External mesh with vertex attributes

ABSTRACT

Methods and systems are disclosed for performing operations for deforming an external mesh. The operations comprise receiving a video that includes a depiction of a real-world object. The operations comprise generating a three-dimensional (3D) body mesh associated with the real-world object that tracks movement of the real-world object across frames of the video. The operations comprise obtaining an external mesh associated with an Augmented-Reality (AR) element. The operations comprise accessing a plurality of deformation attributes associated with the external mesh, each attribute corresponding to a different deformation model. The operations comprise separately deforming, based on respective deformation models, a first portion of the external mesh and a second portion of the external mesh. The operations comprise modifying the video to include a display of the AR element based on the separately deformed first and second portions of the external mesh.

TECHNICAL FIELD

The present disclosure relates generally to providing augmented reality(AR) experiences using a messaging application.

BACKGROUND

Augmented-Reality (AR) is a modification of a virtual environment. Forexample, in Virtual Reality (VR), a user is completely immersed in avirtual world, whereas in AR, the user is immersed in a world wherevirtual objects are combined or superimposed on the real world. An ARsystem aims to generate and present virtual objects that interactrealistically with a real-world environment and with each other.Examples of AR applications can include single or multiple player videogames, instant messaging systems, and the like.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. To easily identifythe discussion of any particular element or act, the most significantdigit or digits in a reference number refer to the figure number inwhich that element is first introduced. Some nonlimiting examples areillustrated in the figures of the accompanying drawings in which:

FIG. 1 is a diagrammatic representation of a networked environment inwhich the present disclosure may be deployed, in accordance with someexamples.

FIG. 2 is a diagrammatic representation of a messaging clientapplication, in accordance with some examples.

FIG. 3 is a diagrammatic representation of a data structure asmaintained in a database, in accordance with some examples.

FIG. 4 is a diagrammatic representation of a message, in accordance withsome examples.

FIG. 5 is a block diagram showing an example external mesh deformationsystem, according to some examples.

FIGS. 6, 7, and 8 are diagrammatic representations of outputs of theexternal mesh deformation system, in accordance with some examples.

FIG. 9 is a flowchart illustrating example operations of the externalmesh deformation system, according to some examples.

FIG. 10 is a diagrammatic representation of a machine in the form of acomputer system within which a set of instructions may be executed forcausing the machine to perform any one or more of the methodologiesdiscussed herein, in accordance with some examples.

FIG. 11 is a block diagram showing a software architecture within whichexamples may be implemented.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative examples of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of various examples.It will be evident, however, to those skilled in the art, that examplesmay be practiced without these specific details. In general, well-knowninstruction instances, protocols, structures, and techniques are notnecessarily shown in detail.

Typically, VR and AR systems display images representing a given user bycapturing an image of the user and, in addition, obtaining a depth mapusing a depth sensor of the real-world human body depicted in the image.By processing the depth map and the image together, the VR and ARsystems can detect positioning of a user in the image and canappropriately modify the user or background in the images. While suchsystems work well, the need for a depth sensor limits the scope of theirapplications. This is because adding depth sensors to user devices forthe purpose of modifying images increases the overall cost andcomplexity of the devices, making them less attractive.

Certain systems do away with the need to use depth sensors to modifyimages. For example, certain systems allow users to replace a backgroundin a videoconference in which a face of the user is detected.Specifically, such systems can use specialized techniques that areoptimized for recognizing a face of a user to identify the background inthe images that depict the user's face. These systems can then replaceonly those pixels that depict the background so that the real-worldbackground is replaced with an alternate background in the images.However, such systems are generally incapable of recognizing a wholebody of a user. As such, if the user is more than a threshold distancefrom the camera such that more than just the face of the user iscaptured by the camera, the replacement of the background with analternate background begins to fail. In such cases, the image quality isseverely impacted, and portions of the face and body of the user can beinadvertently removed by the system as the system falsely identifiessuch portions as belonging to the background rather than the foregroundof the images. Also, such systems fail to properly replace thebackground when more than one user is depicted in the image or videofeed. Because such systems are generally incapable of distinguishing awhole body of a user in an image from a background, these systems arealso unable to apply visual effects to certain portions of a user'sbody, such as articles of clothing or fashion accessories (e.g.,jewelry, handbags, purses, and so forth).

Some AR systems allow AR graphics to be added to an image or video toprovide engaging AR experiences. Such systems can receive the ARgraphics from a designer and can scale and position the AR graphicswithin the image or video. In order to improve the placement andpositioning of the AR graphics on a person depicted in the image orvideo, such systems detect a person depicted in the image or video andgenerate a rig representing bones of the person. This rig is then usedto adjust the AR graphics based on changes in movement to the rig. Whilesuch approaches generally work well, the need for generating a rig of aperson in real time to adjust AR graphics placement increases processingcomplexities and power and memory requirements. This makes such systemsinefficient or incapable of running on small scale mobile deviceswithout sacrificing computing resources or processing speed. Also, therig only represents movement of skeletal or bone structures of a personin the image or video and does not take into account any sort ofexternal physical properties of the person, such as density, weight,skin attributes, and so forth. As such, any AR graphics in these systemscan be adjusted in scale and positioning but cannot be deformed based onother physical properties of the person. In addition, an AR graphicsdesigner typically needs to create a compatible rig for their AR graphicor AR fashion item.

The disclosed techniques improve the efficiency of using the electronicdevice by generating a body mesh of an object, such as a person,depicted in the image and deforming an external mesh in correspondencewith the body mesh. By deforming an external mesh based on changes tothe body mesh of a depicted object, the disclosed techniques can applyone or more visual effects to the image or video in association with theperson depicted in the image or video in a more efficient manner andwithout the need for generating a rig or bone structures of the depictedobject. Particularly, the disclosed techniques can apply one or more ARelements to a person or object depicted in the image or video and thenmodify the one or more AR elements based on movement of the object asdetermined by changes to the body mesh of the object.

The disclosed techniques can also deform or modify different portions ofthe AR elements separately based on different criteria or attributesassociated with such portions. For example, a first portion of the ARelement that is attached or overlaps the depicted object (e.g., a strapof a purse) can be deformed or modified based on changes to thethree-dimensional (3D) body mesh of the object. A second portion of theAR element can extend beyond and dangle away from the depicted objectand/or the first portion of the AR element and can be deformed (togetherwith, simultaneously with, and/or separate from) the first portion basedon information associated with an external force model (e.g., a physicssimulation model, a collision simulation model, chain physics, a clothsimulation model, gravity displacement, and so forth). In an example,the disclosed techniques can access attribute information for eachportion of the AR element. Based on the attribute information, thedisclosed techniques can select a deformation model that is used todeform the respective portion of the AR element. In this way, differentportions of the AR element can be deformed separately and usingdifferent deformation models based on the attributes specified for suchportions. In an example, the attributes information can include anycombination of garment location metric, a garment looseness metric, abody mesh density threshold, or a distance threshold. The deformationmodels can include any combination of an external force model and/or areal-world body movement model.

This simplifies the process of adding AR graphics to an image or videowhich significantly reduces design constraints and costs in generatingsuch AR graphics and decreases the amount of processing complexities andpower and memory requirements. This also improves the illusion of the ARgraphics being part of a real-world environment depicted in an image orvideo that depicts the object. This enables seamless and efficientaddition of AR graphics to an underlying image or video in real time onsmall scale mobile devices. The disclosed techniques can be appliedexclusively or mostly on a mobile device without the need for the mobiledevice to send images/videos to a server. In other examples, thedisclosed techniques are applied exclusively or mostly on a remoteserver or can be divided between a mobile device and a server.

Also, the disclosed techniques allow an AR graphics designer to generatean external mesh for their AR graphics without creating a compatible rigfor the AR graphics which saves time, effort, and creation complexity.The disclosed techniques enable the AR graphics (AR fashion items) to bedeformed with the user's shape (weight, height, body shape, and soforth) by creating a correspondence between a body mesh and an externalmesh of an AR graphic or AR fashion item. The disclosed techniques alsoenable a designer to specify attributes of the AR fashion item to causecertain portions of the AR graphics (by way of deforming the associatedexternal mesh) to be modified or deformed based on an external forcemodel rather than based on the body mesh and/or in combination with bodymesh movement information. For example, the designer can specify that aportion of an AR dress that is more than a certain threshold distanceaway from a torso of a body be deformed based on an external force modeland a second portion of the dress that is within the certain thresholddistance be deformed in accordance with movement of the 3D body meshportion over which the second portion is placed. In an implementation,the external force model can leverage information associated withmovement of the body mesh model to compute modifications anddeformations to the portion of the external mesh (and associated ARgraphics) that is associated with the external force model.

As a result, a realistic display can be provided that shows the userwearing an AR fashion item while deforming the AR fashion item based onthree-dimensional (3D) movement of the user, including changes to thebody shape, body state, body properties, position, and rotation, in away that is intuitive for the user to interact with and select. As usedherein, “article of clothing,” “fashion item,” and “garment” are usedinterchangeably and should be understood to have the same meaning. Thisimproves the overall experience of the user in using the electronicdevice. Also, by providing such AR experiences without using a depthsensor, the overall amount of system resources needed to accomplish atask is reduced.

Networked Computing Environment

FIG. 1 is a block diagram showing an example messaging system 100 forexchanging data (e.g., messages and associated content) over a network.The messaging system 100 includes multiple instances of a client device102, each of which hosts a number of applications, including a messagingclient 104 and other external applications 109 (e.g., third-partyapplications). Each messaging client 104 is communicatively coupled toother instances of the messaging client 104 (e.g., hosted on respectiveother client devices 102), a messaging server system 108 and externalapp(s) servers 110 via a network 112 (e.g., the Internet). A messagingclient 104 can also communicate with locally-hosted third-partyapplications, such as external apps 109 using Application ProgrammingInterfaces (APIs).

A messaging client 104 is able to communicate and exchange data withother messaging clients 104 and with the messaging server system 108 viathe network 112. The data exchanged between messaging clients 104, andbetween a messaging client 104 and the messaging server system 108,includes functions (e.g., commands to invoke functions) as well aspayload data (e.g., text, audio, video or other multimedia data).

The messaging server system 108 provides server-side functionality viathe network 112 to a particular messaging client 104. While certainfunctions of the messaging system 100 are described herein as beingperformed by either a messaging client 104 or by the messaging serversystem 108, the location of certain functionality either within themessaging client 104 or the messaging server system 108 may be a designchoice. For example, it may be technically preferable to initiallydeploy certain technology and functionality within the messaging serversystem 108 but to later migrate this technology and functionality to themessaging client 104 where a client device 102 has sufficient processingcapacity.

The messaging server system 108 supports various services and operationsthat are provided to the messaging client 104. Such operations includetransmitting data to, receiving data from, and processing data generatedby the messaging client 104. This data may include message content,client device information, geolocation information, media augmentationand overlays, message content persistence conditions, social networkinformation, and live event information, as examples. Data exchangeswithin the messaging system 100 are invoked and controlled throughfunctions available via user interfaces (UIs) of the messaging client104.

Turning now specifically to the messaging server system 108, an APIserver 116 is coupled to, and provides a programmatic interface to,application servers 114. The application servers 114 are communicativelycoupled to a database server 120, which facilitates access to a database126 that stores data associated with messages processed by theapplication servers 114. Similarly, a web server 128 is coupled to theapplication servers 114 and provides web-based interfaces to theapplication servers 114. To this end, the web server 128 processesincoming network requests over the Hypertext Transfer Protocol (HTTP)and several other related protocols.

The API server 116 receives and transmits message data (e.g., commandsand message payloads) between the client device 102 and the applicationservers 114. Specifically, the API server 116 provides a set ofinterfaces (e.g., routines and protocols) that can be called or queriedby the messaging client 104 in order to invoke functionality of theapplication servers 114. The API server 116 exposes various functionssupported by the application servers 114, including accountregistration; login functionality; the sending of messages, via theapplication servers 114, from a particular messaging client 104 toanother messaging client 104; the sending of media files (e.g., imagesor video) from a messaging client 104 to a messaging server 118, and forpossible access by another messaging client 104; the settings of acollection of media data (e.g., story); the retrieval of a list offriends of a user of a client device 102; the retrieval of suchcollections; the retrieval of messages and content; the addition anddeletion of entities (e.g., friends) to an entity graph (e.g., a socialgraph); the location of friends within a social graph; and opening anapplication event (e.g., relating to the messaging client 104).

The application servers 114 host a number of server applications andsubsystems, including, for example, a messaging server 118, an imageprocessing server 122, and a social network server 124. The messagingserver 118 implements a number of message processing technologies andfunctions, particularly related to the aggregation and other processingof content (e.g., textual and multimedia content) included in messagesreceived from multiple instances of the messaging client 104. As will bedescribed in further detail, the text and media content from multiplesources may be aggregated into collections of content (e.g., calledstories or galleries). These collections are then made available to themessaging client 104. Other processor- and memory-intensive processingof data may also be performed server-side by the messaging server 118,in view of the hardware requirements for such processing.

The application servers 114 also include an image processing server 122that is dedicated to performing various image processing operations,typically with respect to images or video within the payload of amessage sent from or received at the messaging server 118.

Image processing server 122 is used to implement scan functionality ofthe augmentation system 208 (shown in FIG. 2 ). Scan functionalityincludes activating and providing one or more AR experiences on a clientdevice 102 when an image is captured by the client device 102.Specifically, the messaging client 104 on the client device 102 can beused to activate a camera. The camera displays one or more real-timeimages or a video to a user along with one or more icons or identifiersof one or more AR experiences. The user can select a given one of theidentifiers to launch the corresponding AR experience or perform adesired image modification (e.g., replacing a garment being worn by auser in a video or recoloring the garment worn by the user in the videoor modifying the garment based on a gesture performed by the user).

The social network server 124 supports various social networkingfunctions and services and makes these functions and services availableto the messaging server 118. To this end, the social network server 124maintains and accesses an entity graph 308 (as shown in FIG. 3 ) withinthe database 126. Examples of functions and services supported by thesocial network server 124 include the identification of other users ofthe messaging system 100 with which a particular user has relationshipsor is “following” and also the identification of other entities andinterests of a particular user.

Returning to the messaging client 104, features and functions of anexternal resource (e.g., a third-party application 109 or applet) aremade available to a user via an interface of the messaging client 104.The messaging client 104 receives a user selection of an option tolaunch or access features of an external resource (e.g., a third-partyresource), such as external apps 109. The external resource may be athird-party application (external apps 109) installed on the clientdevice 102 (e.g., a “native app”), or a small-scale version of thethird-party application (e.g., an “applet”) that is hosted on the clientdevice 102 or remote of the client device 102 (e.g., on third-partyservers 110). The small-scale version of the third-party applicationincludes a subset of features and functions of the third-partyapplication (e.g., the full-scale, native version of the third-partystandalone application) and is implemented using a markup-languagedocument. In one example, the small-scale version of the third-partyapplication (e.g., an “applet”) is a web-based, markup-language versionof the third-party application and is embedded in the messaging client104. In addition to using markup-language documents (e.g., a .*ml file),an applet may incorporate a scripting language (e.g., a .*js file or a.json file) and a style sheet (e.g., a .*ss file).

In response to receiving a user selection of the option to launch oraccess features of the external resource (external app 109), themessaging client 104 determines whether the selected external resourceis a web-based external resource or a locally-installed externalapplication. In some cases, external applications 109 that are locallyinstalled on the client device 102 can be launched independently of andseparately from the messaging client 104, such as by selecting an icon,corresponding to the external application 109, on a home screen of theclient device 102. Small-scale versions of such external applicationscan be launched or accessed via the messaging client 104 and, in someexamples, no or limited portions of the small-scale external applicationcan be accessed outside of the messaging client 104. The small-scaleexternal application can be launched by the messaging client 104receiving, from an external app(s) server 110, a markup-languagedocument associated with the small-scale external application andprocessing such a document.

In response to determining that the external resource is alocally-installed external application 109, the messaging client 104instructs the client device 102 to launch the external application 109by executing locally-stored code corresponding to the externalapplication 109. In response to determining that the external resourceis a web-based resource, the messaging client 104 communicates with theexternal app(s) servers 110 to obtain a markup-language documentcorresponding to the selected resource. The messaging client 104 thenprocesses the obtained markup-language document to present the web-basedexternal resource within a user interface of the messaging client 104.

The messaging client 104 can notify a user of the client device 102, orother users related to such a user (e.g., “friends”), of activity takingplace in one or more external resources. For example, the messagingclient 104 can provide participants in a conversation (e.g., a chatsession) in the messaging client 104 with notifications relating to thecurrent or recent use of an external resource by one or more members ofa group of users. One or more users can be invited to join in an activeexternal resource or to launch a recently-used but currently inactive(in the group of friends) external resource. The external resource canprovide participants in a conversation, each using a respectivemessaging client 104, with the ability to share an item, status, state,or location in an external resource with one or more members of a groupof users into a chat session. The shared item may be an interactive chatcard with which members of the chat can interact, for example, to launchthe corresponding external resource, view specific information withinthe external resource, or take the member of the chat to a specificlocation or state within the external resource. Within a given externalresource, response messages can be sent to users on the messaging client104. The external resource can selectively include different media itemsin the responses, based on a current context of the external resource.

The messaging client 104 can present a list of the available externalresources (e.g., third-party or external applications 109 or applets) toa user to launch or access a given external resource. This list can bepresented in a context-sensitive menu. For example, the iconsrepresenting different ones of the external application 109 (or applets)can vary based on how the menu is launched by the user (e.g., from aconversation interface or from a non-conversation interface).

The messaging client 104 can present, to a user, one or more ARexperiences. As an example, the messaging client 104 can detect a personin an image or video captured by the client device 102. The messagingclient 104 can generate a body mesh for the person depicted in the imageor video. The body mesh can be a 3D mesh, or polygon mesh, that includesa collection of vertices, edges, and faces that define the shape of apolyhedral object depicted in the image or video. The mesh can be acollection of several closed surfaces. In a mathematical vectoralgebraic sense, which may be important for calculations, a mesh can bea collection of numbers organized into several matrices. In a geometricdescription, a mesh can be made of points that are joined together withsegments and surfaced by polygons.

The messaging client 104 can receive a user selection of an AR graphicto add to the image or video. The messaging client 104 can obtain anexternal mesh associated with the AR graphic. The AR graphic canrepresent a fashion accessory or other item that has a first portionattached to a depicted object, such as a person, and a second portionthat hangs freely or dangles from the first portion of the depictedobject or in which the entire fashion item dangles freely from thedepicted real-world object. For example, the AR graphic can representearrings which are attached to a person's ears or other body part andhave a portion that dangles freely in the air. For example, the ARgraphic can represent a belt which wraps around a waist of a person'sbody or other body part and has a portion that dangles freely in theair. For example, the AR graphic can represent a hair tie which wrapsaround hair of a person's body or other body part and has a portion thatdangles freely in the air. For example, the AR graphic can represent afantasy item or object that is attached to a person's body or other bodypart (such as an AR tail, extra limbs, extra head, long fur, and soforth) and has a portion that dangles freely in the air. The AR graphiccan represent bunny ears that are attached to the person at one end anddangle freely at another end. The AR graphic can represent a purse orhandbag which has a strap that overlaps or is attached to a body of aperson depicted in the image or video and that has a container portion(the purse) that dangles freely from the strap. The AR graphic canrepresent a shirt or other garment that has a first looseness metricindicating how tight or loose the garment is when worn by a depictedperson. The AR graphic can represent a shirt or other garment that has asecond looseness metric that is greater (indicating more loose) or lessthan (indicating tighter) than the first looseness metric. The ARgraphic can represent a dress that has a first portion close to thetorso of the person depicted in the image having a first loosenessmetric (e.g., being tight on the person) and a second portion close tothe legs and away from the torso by more than a threshold having asecond looseness metric (e.g., being loose around the legs).

The external mesh associated with the AR graphic can include differentportions that are deformed separately based on whether the portions areattached or associated with the object depicted in the image or video ordangle freely from the object depicted in the image or video. Thedifferent portions can be associated with different deformationattributes that can be specified by a designer of the AR graphic. Eachdifferent deformation attribute defines the deformation model used todeform the corresponding portion of the AR graphic. As an example, theplurality of deformation attributes can correspond to at least one of agarment location metric, a garment looseness metric, a body mesh densitythreshold, or a distance threshold, and the deformation model caninclude an external force model or a real-world body movement model(e.g., body movement model).

The messaging client 104 can automatically establish a correspondencebetween the body mesh (e.g., 3D body mesh) and the external mesh. Themessaging client 104 can position the external mesh over or with respectto the 3D body mesh within the image or video. The messaging client 104can determine (based on placement information associated with theexternal mesh) a first portion or first set of portions that aredeformed based on movement information associated with the 3D body mesh,such as based on a first deformation attribute associated with the firstportion or first set of portions. The messaging client 104 can determine(based on placement information associated with the external mesh) asecond portion or second set of portions that are deformed based on anexternal force simulation separately from deforming the first portion orfirst set of portions based on the movement information associated withthe 3D body mesh, such as based on a second deformation attributeassociated with the second portion or second set of portions.

The messaging client 104 can then display the AR graphic (which has beendeformed based on the deformation attributes of the external mesh)within the image or video. This provides the user with a realisticdisplay of the image or video depiction of the person combined with theselected AR graphic that has different portions moving in different ways(either based on movement of the person or application of an externalforce, such as gravity, cloth simulation, or collision). In an example,the AR graphic can be a fashion item, such as a shirt, pants, skirt,dress, jewelry, purse, furniture item, household item, eyewear,eyeglasses, AR logos, AR emblems, or any other suitable item or object.While the disclosed examples are discussed in relation to an AR dress(or user of the client device 102) that is added to an image or video,similar techniques can be applied to any other AR items or article ofclothing or fashion item, such as a purse, pants, shorts, skirts,jackets, t-shirts, blouses, glasses, jewelry, earrings, bunny ears, ahat, ear muffs, and so forth.

In this way, the messaging client 104 can adjust an external mesh (andas a result the AR graphic associated with the external mesh) in realtime based on movements and other changes (e.g., changes to the bodyshape, position, rotation and scale) of a body mesh associated with anobject, such as a person, depicted in the image or video and based onapplication of external forces. This provides an illusion that the ARgraphic is actually included in the real-world environment depicted inthe image or video which improves the overall user experience. Furtherdetails of the deformation of the external mesh with respect to the bodymesh and external forces are provided below in connection with FIG. 5 .

System Architecture

FIG. 2 is a block diagram illustrating further details regarding themessaging system 100, according to some examples. Specifically, themessaging system 100 is shown to comprise the messaging client 104 andthe application servers 114. The messaging system 100 embodies a numberof subsystems, which are supported on the client side by the messagingclient 104 and on the sever side by the application servers 114. Thesesubsystems include, for example, an ephemeral timer system 202, acollection management system 204, an augmentation system 208, a mapsystem 210, a game system 212, and an external resource system 220.

The ephemeral timer system 202 is responsible for enforcing thetemporary or time-limited access to content by the messaging client 104and the messaging server 118. The ephemeral timer system 202incorporates a number of timers that, based on duration and displayparameters associated with a message, or collection of messages (e.g., astory), selectively enable access (e.g., for presentation and display)to messages and associated content via the messaging client 104. Furtherdetails regarding the operation of the ephemeral timer system 202 areprovided below.

The collection management system 204 is responsible for managing sets orcollections of media (e.g., collections of text, image video, and audiodata). A collection of content (e.g., messages, including images, video,text, and audio) may be organized into an “event gallery” or an “eventstory.” Such a collection may be made available for a specified timeperiod, such as the duration of an event to which the content relates.For example, content relating to a music concert may be made availableas a “story” for the duration of that music concert. The collectionmanagement system 204 may also be responsible for publishing an iconthat provides notification of the existence of a particular collectionto the user interface of the messaging client 104.

The collection management system 204 further includes a curationinterface 206 that allows a collection manager to manage and curate aparticular collection of content. For example, the curation interface206 enables an event organizer to curate a collection of contentrelating to a specific event (e.g., delete inappropriate content orredundant messages). Additionally, the collection management system 204employs machine vision (or image recognition technology) and contentrules to automatically curate a content collection. In certain examples,compensation may be paid to a user for the inclusion of user-generatedcontent into a collection. In such cases, the collection managementsystem 204 operates to automatically make payments to such users for theuse of their content.

The augmentation system 208 provides various functions that enable auser to augment (e.g., annotate or otherwise modify or edit) mediacontent associated with a message. For example, the augmentation system208 provides functions related to the generation and publishing of mediaoverlays for messages processed by the messaging system 100. Theaugmentation system 208 operatively supplies a media overlay oraugmentation (e.g., an image filter) to the messaging client 104 basedon a geolocation of the client device 102. In another example, theaugmentation system 208 operatively supplies a media overlay to themessaging client 104 based on other information, such as social networkinformation of the user of the client device 102. A media overlay mayinclude audio and visual content and visual effects. Examples of audioand visual content include pictures, texts, logos, animations, and soundeffects. An example of a visual effect includes color overlaying. Theaudio and visual content or the visual effects can be applied to a mediacontent item (e.g., a photo) at the client device 102. For example, themedia overlay may include text, a graphical element, or an image thatcan be overlaid on top of a photograph taken by the client device 102.In another example, the media overlay includes an identification of alocation overlay (e.g., Venice beach), a name of a live event, or a nameof a merchant overlay (e.g., Beach Coffee House). In another example,the augmentation system 208 uses the geolocation of the client device102 to identify a media overlay that includes the name of a merchant atthe geolocation of the client device 102. The media overlay may includeother indicia associated with the merchant. The media overlays may bestored in the database 126 and accessed through the database server 120.

In some examples, the augmentation system 208 provides a user-basedpublication platform that enables users to select a geolocation on a mapand upload content associated with the selected geolocation. The usermay also specify circumstances under which a particular media overlayshould be offered to other users. The augmentation system 208 generatesa media overlay that includes the uploaded content and associates theuploaded content with the selected geolocation.

In other examples, the augmentation system 208 provides a merchant-basedpublication platform that enables merchants to select a particular mediaoverlay associated with a geolocation via a bidding process. Forexample, the augmentation system 208 associates the media overlay of thehighest bidding merchant with a corresponding geolocation for apredefined amount of time. The augmentation system 208 communicates withthe image processing server 122 to obtain AR experiences and presentsidentifiers of such experiences in one or more user interfaces (e.g., asicons over a real-time image or video or as thumbnails or icons ininterfaces dedicated for presented identifiers of AR experiences). Oncean AR experience is selected, one or more images, videos, or ARgraphical elements are retrieved and presented as an overlay on top ofthe images or video captured by the client device 102. In some cases,the camera is switched to a front-facing view (e.g., the front-facingcamera of the client device 102 is activated in response to activationof a particular AR experience) and the images from the front-facingcamera of the client device 102 start being displayed on the clientdevice 102 instead of the rear-facing camera of the client device 102.The one or more images, videos, or AR graphical elements are retrievedand presented as an overlay on top of the images that are captured anddisplayed by the front-facing camera of the client device 102.

In other examples, the augmentation system 208 is able to communicateand exchange data with another augmentation system 208 on another clientdevice 102 and with the server via the network 112. The data exchangedcan include a session identifier that identifies the shared AR session,a transformation between a first client device 102 and a second clientdevice 102 (e.g., a plurality of client devices 102 include the firstand second devices) that is used to align the shared AR session to acommon point of origin, a common coordinate frame, functions (e.g.,commands to invoke functions), and other payload data (e.g., text,audio, video or other multimedia data).

The augmentation system 208 sends the transformation to the secondclient device 102 so that the second client device 102 can adjust the ARcoordinate system based on the transformation. In this way, the firstand second client devices 102 synch up their coordinate systems andframes for displaying content in the AR session. Specifically, theaugmentation system 208 computes the point of origin of the secondclient device 102 in the coordinate system of the first client device102. The augmentation system 208 can then determine an offset in thecoordinate system of the second client device 102 based on the positionof the point of origin from the perspective of the second client device102 in the coordinate system of the second client device 102. Thisoffset is used to generate the transformation so that the second clientdevice 102 generates AR content according to a common coordinate systemor frame as the first client device 102.

The augmentation system 208 can communicate with the client device 102to establish individual or shared AR sessions. The augmentation system208 can also be coupled to the messaging server 118 to establish anelectronic group communication session (e.g., group chat, instantmessaging) for the client devices 102 in a shared AR session. Theelectronic group communication session can be associated with a sessionidentifier provided by the client devices 102 to gain access to theelectronic group communication session and to the shared AR session. Inone example, the client devices 102 first gain access to the electronicgroup communication session and then obtain the session identifier inthe electronic group communication session that allows the clientdevices 102 to access the shared AR session. In some examples, theclient devices 102 are able to access the shared AR session without aidor communication with the augmentation system 208 in the applicationservers 114.

The map system 210 provides various geographic location functions andsupports the presentation of map-based media content and messages by themessaging client 104. For example, the map system 210 enables thedisplay of user icons or avatars (e.g., stored in profile data 316) on amap to indicate a current or past location of “friends” of a user, aswell as media content (e.g., collections of messages includingphotographs and videos) generated by such friends, within the context ofa map. For example, a message posted by a user to the messaging system100 from a specific geographic location may be displayed within thecontext of a map at that particular location to “friends” of a specificuser on a map interface of the messaging client 104. A user canfurthermore share his or her location and status information (e.g.,using an appropriate status avatar) with other users of the messagingsystem 100 via the messaging client 104, with this location and statusinformation being similarly displayed within the context of a mapinterface of the messaging client 104 to selected users.

The game system 212 provides various gaming functions within the contextof the messaging client 104. The messaging client 104 provides a gameinterface providing a list of available games (e.g., web-based games orweb-based applications) that can be launched by a user within thecontext of the messaging client 104 and played with other users of themessaging system 100. The messaging system 100 further enables aparticular user to invite other users to participate in the play of aspecific game, by issuing invitations to such other users from themessaging client 104. The messaging client 104 also supports both voiceand text messaging (e.g., chats) within the context of gameplay,provides a leaderboard for the games, and also supports the provision ofin-game rewards (e.g., coins and items).

The external resource system 220 provides an interface for the messagingclient 104 to communicate with external app(s) servers 110 to launch oraccess external resources. Each external resource (apps) server 110hosts, for example, a markup language (e.g., HTML5) based application orsmall-scale version of an external application (e.g., game, utility,payment, or ride-sharing application that is external to the messagingclient 104). The messaging client 104 may launch a web-based resource(e.g., application) by accessing the HTML5 file from the externalresource (apps) servers 110 associated with the web-based resource. Incertain examples, applications hosted by external resource servers 110are programmed in JavaScript leveraging a Software Development Kit (SDK)provided by the messaging server 118. The SDK includes APIs withfunctions that can be called or invoked by the web-based application. Incertain examples, the messaging server 118 includes a JavaScript librarythat provides a given third-party resource access to certain user dataof the messaging client 104. HTML5 is used as an example technology forprogramming games, but applications and resources programmed based onother technologies can be used.

In order to integrate the functions of the SDK into the web-basedresource, the SDK is downloaded by an external resource (apps) server110 from the messaging server 118 or is otherwise received by theexternal resource (apps) server 110. Once downloaded or received, theSDK is included as part of the application code of a web-based externalresource. The code of the web-based resource can then call or invokecertain functions of the SDK to integrate features of the messagingclient 104 into the web-based resource.

The SDK stored on the messaging server 118 effectively provides thebridge between an external resource (e.g., third-party or externalapplications 109 or applets) and the messaging client 104. This providesthe user with a seamless experience of communicating with other users onthe messaging client 104, while also preserving the look and feel of themessaging client 104. To bridge communications between an externalresource and a messaging client 104, in certain examples, the SDKfacilitates communication between external resource servers 110 and themessaging client 104. In certain examples, a WebViewJavaScriptBridgerunning on a client device 102 establishes two one-way communicationchannels between an external resource and the messaging client 104.Messages are sent between the external resource and the messaging client104 via these communication channels asynchronously. Each SDK functioninvocation is sent as a message and callback. Each SDK function isimplemented by constructing a unique callback identifier and sending amessage with that callback identifier.

By using the SDK, not all information from the messaging client 104 isshared with external resource servers 110. The SDK limits whichinformation is shared based on the needs of the external resource. Incertain examples, each external resource server 110 provides an HTML5file corresponding to the web-based external resource to the messagingserver 118. The messaging server 118 can add a visual representation(such as a box art or other graphic) of the web-based external resourcein the messaging client 104. Once the user selects the visualrepresentation or instructs the messaging client 104 through a GUI ofthe messaging client 104 to access features of the web-based externalresource, the messaging client 104 obtains the HTML5 file andinstantiates the resources necessary to access the features of theweb-based external resource.

The messaging client 104 presents a graphical user interface (e.g., alanding page or title screen) for an external resource. During, before,or after presenting the landing page or title screen, the messagingclient 104 determines whether the launched external resource has beenpreviously authorized to access user data of the messaging client 104.In response to determining that the launched external resource has beenpreviously authorized to access user data of the messaging client 104,the messaging client 104 presents another graphical user interface ofthe external resource that includes functions and features of theexternal resource. In response to determining that the launched externalresource has not been previously authorized to access user data of themessaging client 104, after a threshold period of time (e.g., 3 seconds)of displaying the landing page or title screen of the external resource,the messaging client 104 slides up (e.g., animates a menu as surfacingfrom a bottom of the screen to a middle of or other portion of thescreen) a menu for authorizing the external resource to access the userdata. The menu identifies the type of user data that the externalresource will be authorized to use. In response to receiving a userselection of an accept option, the messaging client 104 adds theexternal resource to a list of authorized external resources and allowsthe external resource to access user data from the messaging client 104.In some examples, the external resource is authorized by the messagingclient 104 to access the user data in accordance with an OAuth 2framework.

The messaging client 104 controls the type of user data that is sharedwith external resources based on the type of external resource beingauthorized. For example, external resources that include full-scaleexternal applications (e.g., a third-party or external application 109)are provided with access to a first type of user data (e.g., onlytwo-dimensional (2D) avatars of users with or without different avatarcharacteristics). As another example, external resources that includesmall-scale versions of external applications (e.g., web-based versionsof third-party applications) are provided with access to a second typeof user data (e.g., payment information, 2D avatars of users, 3D avatarsof users, and avatars with various avatar characteristics). Avatarcharacteristics include different ways to customize a look and feel ofan avatar, such as different poses, facial features, clothing, and soforth.

An external mesh deformation system 224 deforms an external mesh basedon changes to a 3D/2D body mesh of an object depicted in an image orvideo in real time and based on an external force simulation model(external force model). In an example, the external mesh deformationsystem 224 deforms a first portion of the external mesh that isassociated with a first deformation attribute based on a firstdeformation model, such as based on movement information associated withthe body mesh. The external mesh deformation system 224 deforms a secondportion of the external mesh that is associated with a seconddeformation attribute based on a second deformation model, such as basedon an external force simulation model. In an example, in response todeforming different portions of the external mesh based on differentdeformation models, the external mesh deformation system 224 can presentan AR graphic associated with the external mesh in the image or video,such as by presenting a fashion item fitted to a user depicted in animage (or video) or multiple AR fashion items on top of multiple usersdepicted in an image (or video) where different portions of the ARfashion item or graphic move in different ways (some dependent on themovement of the real-world object and others based on an external forcemodel, such as collision or cloth simulation or gravity). In someexamples, the external mesh deformation system 224 can add additionalvisual effects to the AR graphic, such as particles or sparkles, thatmove based on the external force simulation model in similar ways as theAR graphic is moved. An illustrative implementation of the external meshdeformation system 224 is shown and described in connection with FIG. 5below.

Specifically, the external mesh deformation system 224 is a componentthat can be accessed by an AR/VR application implemented on the clientdevice 102. The AR/VR application uses an RGB camera to capture amonocular image of a user. The AR/VR application applies various trainedmachine learning techniques on the captured image of the user togenerate a 3D body mesh representing the user depicted in the image andto apply one or more AR visual effects to the captured image bydeforming one or more external meshes associated with the AR visualeffects. In some implementations, the AR/VR application continuouslycaptures images of the user and updates the 3D body mesh and externalmesh(es) in real time or periodically to continuously or periodicallyupdate the applied one or more visual effects. This allows the user tomove around in the real world and see the one or more visual effectsupdate in real time. In some examples, the external mesh deformationsystem 224 automatically establishes a correspondence between theexternal mesh and the 3D body mesh once prior to runtime (e.g., beforethe AR graphics are presented to the user), and then the external meshand the 3D body mesh are deformed with respect to each other duringruntime to update the display of the AR graphics associated with theexternal mesh. In other examples, the automated correspondence cancontinuously be updated and generated during runtime while alsodeforming the external mesh.

In training, the external mesh deformation system 224 obtains a firstplurality of input training images that include depictions of one ormore users having different body types and characteristics. Thesetraining images also provide the ground truth information including bodymeshes corresponding to the one or more users depicted in each image. Amachine learning technique (e.g., a deep neural network) is trainedbased on features of the plurality of training images. Specifically, themachine learning technique extracts one or more features from a giventraining image and estimates a 3D body mesh for the user depicted in thegiven training image. The machine learning technique obtains the groundtruth information including the 3D body mesh corresponding to thetraining image and adjusts or updates one or more coefficients orparameters to improve subsequent estimations of body meshes.

Data Architecture

FIG. 3 is a schematic diagram illustrating data structures 300, whichmay be stored in the database 126 of the messaging server system 108,according to certain examples. While the content of the database 126 isshown to comprise a number of tables, it will be appreciated that thedata could be stored in other types of data structures (e.g., as anobject-oriented database).

The database 126 includes message data stored within a message table302. This message data includes, for any particular one message, atleast message sender data, message recipient (or receiver) data, and apayload. Further details regarding information that may be included in amessage, and included within the message data stored in the messagetable 302, are described below with reference to FIG. 4 .

An entity table 306 stores entity data and is linked (e.g.,referentially) to an entity graph 308 and profile data 316. Entities forwhich records are maintained within the entity table 306 may includeindividuals, corporate entities, organizations, objects, places, events,and so forth. Regardless of entity type, any entity regarding which themessaging server system 108 stores data may be a recognized entity. Eachentity is provided with a unique identifier, as well as an entity typeidentifier (not shown).

The entity graph 308 stores information regarding relationships andassociations between entities. Such relationships may be social,professional (e.g., work at a common corporation or organization),interest-based, or activity-based, merely for example.

The profile data 316 stores multiple types of profile data about aparticular entity. The profile data 316 may be selectively used andpresented to other users of the messaging system 100, based on privacysettings specified by a particular entity. Where the entity is anindividual, the profile data 316 includes, for example, a user name,telephone number, address, and settings (e.g., notification and privacysettings), as well as a user-selected avatar representation (orcollection of such avatar representations). A particular user may thenselectively include one or more of these avatar representations withinthe content of messages communicated via the messaging system 100 and onmap interfaces displayed by messaging clients 104 to other users. Thecollection of avatar representations may include “status avatars,” whichpresent a graphical representation of a status or activity that the usermay select to communicate at a particular time.

Where the entity is a group, the profile data 316 for the group maysimilarly include one or more avatar representations associated with thegroup, in addition to the group name, members, and various settings(e.g., notifications) for the relevant group.

The database 126 also stores augmentation data, such as overlays orfilters, in an augmentation table 310. The augmentation data isassociated with and applied to videos (for which data is stored in avideo table 304) and images (for which data is stored in an image table312).

The database 126 can also store data pertaining to individual and sharedAR sessions. This data can include data communicated between an ARsession client controller of a first client device 102 and another ARsession client controller of a second client device 102, and datacommunicated between the AR session client controller and theaugmentation system 208. Data can include data used to establish thecommon coordinate frame of the shared AR scene, the transformationbetween the devices, the session identifier, images depicting a body,skeletal joint positions, wrist joint positions, feet, and so forth.

Filters, in one example, are overlays that are displayed as overlaid onan image or video during presentation to a recipient user. Filters maybe of various types, including user-selected filters from a set offilters presented to a sending user by the messaging client 104 when thesending user is composing a message. Other types of filters includegeolocation filters (also known as geo-filters), which may be presentedto a sending user based on geographic location. For example, geolocationfilters specific to a neighborhood or special location may be presentedwithin a user interface by the messaging client 104, based ongeolocation information determined by a Global Positioning System (GPS)unit of the client device 102.

Another type of filter is a data filter, which may be selectivelypresented to a sending user by the messaging client 104, based on otherinputs or information gathered by the client device 102 during themessage creation process. Examples of data filters include currenttemperature at a specific location, a current speed at which a sendinguser is traveling, battery life for a client device 102, or the currenttime.

Other augmentation data that may be stored within the image table 312includes AR content items (e.g., corresponding to applying ARexperiences). An AR content item or AR item may be a real-time specialeffect and sound that may be added to an image or a video.

As described above, augmentation data includes AR content items,overlays, image transformations, AR images, AR logos or emblems, andsimilar terms that refer to modifications that may be applied to imagedata (e.g., videos or images). This includes real-time modifications,which modify an image as it is captured using device sensors (e.g., oneor multiple cameras) of a client device 102 and then displayed on ascreen of the client device 102 with the modifications. This alsoincludes modifications to stored content, such as video clips in agallery that may be modified. For example, in a client device 102 withaccess to multiple AR content items, a user can use a single video clipwith multiple AR content items to see how the different AR content itemswill modify the stored clip. For example, multiple AR content items thatapply different pseudorandom movement models can be applied to the samecontent by selecting different AR content items for the content.Similarly, real-time video capture may be used with an illustratedmodification to show how video images currently being captured bysensors of a client device 102 would modify the captured data. Such datamay simply be displayed on the screen and not stored in memory, or thecontent captured by the device sensors may be recorded and stored inmemory with or without the modifications (or both). In some systems, apreview feature can show how different AR content items will look withindifferent windows in a display at the same time. This can, for example,enable multiple windows with different pseudorandom animations to beviewed on a display at the same time.

Data and various systems using AR content items or other such transformsystems to modify content using this data can thus involve detection ofreal-world objects (e.g., faces, hands, bodies, cats, dogs, surfaces,objects, etc.), tracking of such objects as they leave, enter, and movearound the field of view in video frames, and the modification ortransformation of such objects as they are tracked. In various examples,different methods for achieving such transformations may be used. Someexamples may involve generating a 3D mesh model of the object or objectsand using transformations and animated textures of the model within thevideo to achieve the transformation. In other examples, tracking ofpoints on an object may be used to place an image or texture (which maybe 2D or 3D) at the tracked position. In still further examples, neuralnetwork analysis of video frames may be used to place images, models, ortextures in content (e.g., images or frames of video). AR content itemsor elements thus refer both to the images, models, and textures used tocreate transformations in content, as well as to additional modeling andanalysis information needed to achieve such transformations with objectdetection, tracking, and placement.

Real-time video processing can be performed with any kind of video data(e.g., video streams, video files, etc.) saved in a memory of acomputerized system of any kind. For example, a user can load videofiles and save them in a memory of a device or can generate a videostream using sensors of the device. Additionally, any objects can beprocessed using a computer animation model, such as a human's face andparts of a human body, animals, or non-living things such as chairs,cars, or other objects.

In some examples, when a particular modification is selected along withcontent to be transformed, elements to be transformed are identified bythe computing device and then detected and tracked if they are presentin the frames of the video. The elements of the object are modifiedaccording to the request for modification, thus transforming the framesof the video stream. Transformation of frames of a video stream can beperformed by different methods for different kinds of transformation.For example, for transformations of frames mostly referring to changingforms of an object's elements, characteristic points for each element ofan object are calculated (e.g., using an Active Shape Model (ASM) orother known methods). Then, a mesh based on the characteristic points isgenerated for each of the at least one element of the object. This meshis used in the following stage of tracking the elements of the object inthe video stream. In the process of tracking, the mentioned mesh foreach element is aligned with a position of each element. Then,additional points are generated on the mesh. A first set of first pointsis generated for each element based on a request for modification, and aset of second points is generated for each element based on the set offirst points and the request for modification. Then, the frames of thevideo stream can be transformed by modifying the elements of the objecton the basis of the sets of first and second points and the mesh. Insuch method, a background of the modified object can be changed ordistorted as well by tracking and modifying the background.

In some examples, transformations changing some areas of an object usingits elements can be performed by calculating characteristic points foreach element of an object and generating a mesh based on the calculatedcharacteristic points. Points are generated on the mesh and then variousareas based on the points are generated. The elements of the object arethen tracked by aligning the area for each element with a position foreach of the at least one element, and properties of the areas can bemodified based on the request for modification, thus transforming theframes of the video stream. Depending on the specific request formodification, properties of the mentioned areas can be transformed indifferent ways. Such modifications may involve changing color of areas;removing at least some part of areas from the frames of the videostream; including one or more new objects into areas which are based ona request for modification; and modifying or distorting the elements ofan area or object. In various examples, any combination of suchmodifications or other similar modifications may be used. For certainmodels to be animated, some characteristic points can be selected ascontrol points to be used in determining the entire state-space ofoptions for the model animation.

In some examples, two meshes associated with different objects can begenerated and deformed in correspondence to each other. A first mesh(also referred to as the body mesh or 3D body mesh) can be associatedwith and represent movements of a real-world object, such as a person,depicted in the image or video. A second mesh (also referred to as anexternal mesh) can be associated with an AR graphic or effect to beapplied to the real-world object. The second mesh can be associated withplacement information that specifies how the second mesh is placed orpositioned in 3D space relative to the first mesh. The placementinformation can capture automatically generated correspondenceinformation based on proximity (controlled by minimum or maximumdistance thresholds or number of controlling vertices) between one ormore vertices of the first mesh and one or more vertices of the secondmesh. The placement information can also be specified in terms of UVspace information that indicates how close or how far to place thesecond mesh in the UV space relative to UV coordinates of the firstmesh. The placement information can also specify deformation attributes,such as indicating a first set of portions to deform based on a firstdeformation model (e.g., based on movement of the corresponding firstmesh) and a second set of portions to deform based on a seconddeformation model (e.g., an external force simulation model). Thedeformation attributes can be used to select the different portions ofthe second mesh and to control how the selected portions are movedrelative to the first mesh. As the first mesh is deformed in real timeduring capture of the image or video, the first and second sets ofportions of the second mesh are similarly deformed (based on changes tothe first mesh and/or outputs of the external force simulation model) toeffectuate a change to the corresponding AR graphic that is rendered fordisplay in the image or video.

In some examples of a computer animation model to transform image datausing body/person detection, the body/person is detected on an imagewith use of a specific body/person detection algorithm (e.g., 3D humanpose estimation and mesh reconstruction processes). Then, an ASMalgorithm is applied to the body/person region of an image to detectbody/person feature reference points.

Other methods and algorithms suitable for body/person detection can beused. For example, in some examples, features are located using alandmark, which represents a distinguishable point present in most ofthe images under consideration. For body/person landmarks, for example,the location of the left arm may be used. If an initial landmark is notidentifiable, secondary landmarks may be used. Such landmarkidentification procedures may be used for any such objects. In someexamples, a set of landmarks forms a shape. Shapes can be represented asvectors using the coordinates of the points in the shape. One shape isaligned to another with a similarity transform (allowing translation,scaling, and rotation) that minimizes the average Euclidean distancebetween shape points. The mean shape is the mean of the aligned trainingshapes.

In some examples, a search is started for landmarks from the mean shapealigned to the position and size of the body/person determined by aglobal body/person detector. Such a search then repeats the steps ofsuggesting a tentative shape by adjusting the locations of shape pointsby template matching of the image texture around each point and thenconforming the tentative shape to a global shape model until convergenceoccurs. In some systems, individual template matches are unreliable, andthe shape model pools the results of the weak template matches to form astronger overall classifier. The entire search is repeated at each levelin an image pyramid, from coarse to fine resolution.

A transformation system can capture an image or video stream on a clientdevice (e.g., the client device 102) and perform complex imagemanipulations locally on the client device 102 while maintaining asuitable user experience, computation time, and power consumption. Thecomplex image manipulations may include size and shape changes, emotiontransfers (e.g., changing a face from a frown to a smile), statetransfers (e.g., aging a subject, reducing apparent age, changinggender), style transfers, graphical element application, 3D human poseestimation, 3D body mesh reconstruction, and any other suitable image orvideo manipulation implemented by a convolutional neural network thathas been configured to execute efficiently on the client device 102.

In some examples, a computer animation model to transform image data canbe used by a system where a user may capture an image or video stream ofthe user (e.g., a selfie) using a client device 102 having a neuralnetwork operating as part of a messaging client 104 operating on theclient device 102. The transformation system operating within themessaging client 104 determines the presence of a body/person within theimage or video stream and provides modification icons associated with acomputer animation model to transform image data, or the computeranimation model can be present as associated with an interface describedherein. The modification icons include changes that may be the basis formodifying the user's body/person within the image or video stream aspart of the modification operation. Once a modification icon isselected, the transformation system initiates a process to convert theimage of the user to reflect the selected modification icon (e.g.,generate a smiling face on the user). A modified image or video streammay be presented in a graphical user interface displayed on the clientdevice 102 as soon as the image or video stream is captured and aspecified modification is selected. The transformation system mayimplement a complex convolutional neural network on a portion of theimage or video stream to generate and apply the selected modification.That is, the user may capture the image or video stream and be presentedwith a modified result in real-time or near real-time once amodification icon has been selected. Further, the modification may bepersistent while the video stream is being captured and the selectedmodification icon remains toggled. Machine-taught neural networks may beused to enable such modifications.

The graphical user interface, presenting the modification performed bythe transformation system, may supply the user with additionalinteraction options. Such options may be based on the interface used toinitiate the content capture and selection of a particular computeranimation model (e.g., initiation from a content creator userinterface). In various examples, a modification may be persistent afteran initial selection of a modification icon. The user may toggle themodification on or off by tapping or otherwise selecting the body/personbeing modified by the transformation system and store it for laterviewing or browse to other areas of the imaging application. Wheremultiple faces are modified by the transformation system, the user maytoggle the modification on or off globally by tapping or selecting asingle body/person modified and displayed within a graphical userinterface. In some examples, individual bodies/persons, among a group ofmultiple bodies/persons, may be individually modified, or suchmodifications may be individually toggled by tapping or selecting theindividual body/person or a series of individual bodies/personsdisplayed within the graphical user interface.

A story table 314 stores data regarding collections of messages andassociated image, video, or audio data, which are compiled into acollection (e.g., a story or a gallery). The creation of a particularcollection may be initiated by a particular user (e.g., each user forwhich a record is maintained in the entity table 306). A user may createa “personal story” in the form of a collection of content that has beencreated and sent/broadcast by that user. To this end, the user interfaceof the messaging client 104 may include an icon that is user-selectableto enable a sending user to add specific content to his or her personalstory.

A collection may also constitute a “live story,” which is a collectionof content from multiple users that is created manually, automatically,or using a combination of manual and automatic techniques. For example,a “live story” may constitute a curated stream of user-submitted contentfrom various locations and events. Users whose client devices havelocation services enabled and are at a common location event at aparticular time may, for example, be presented with an option, via auser interface of the messaging client 104, to contribute content to aparticular live story. The live story may be identified to the user bythe messaging client 104, based on his or her location. The end resultis a “live story” told from a community perspective.

A further type of content collection is known as a “location story,”which enables a user whose client device 102 is located within aspecific geographic location (e.g., on a college or university campus)to contribute to a particular collection. In some examples, acontribution to a location story may require a second degree ofauthentication to verify that the end user belongs to a specificorganization or other entity (e.g., is a student on the universitycampus).

As mentioned above, the video table 304 stores video data that, in oneexample, is associated with messages for which records are maintainedwithin the message table 302. Similarly, the image table 312 storesimage data associated with messages for which message data is stored inthe entity table 306. The entity table 306 may associate variousaugmentations from the augmentation table 310 with various images andvideos stored in the image table 312 and the video table 304.

Trained machine learning technique(s) 307 stores parameters that havebeen trained during training of the external mesh deformation system224. For example, trained machine learning techniques 307 stores thetrained parameters of one or more neural network machine learningtechniques.

Data Communications Architecture

FIG. 4 is a schematic diagram illustrating a structure of a message 400,according to some examples, generated by a messaging client 104 forcommunication to a further messaging client 104 or the messaging server118. The content of a particular message 400 is used to populate themessage table 302 stored within the database 126, accessible by themessaging server 118. Similarly, the content of a message 400 is storedin memory as “in-transit” or “in-flight” data of the client device 102or the application servers 114. A message 400 is shown to include thefollowing example components:

-   -   message identifier 402: a unique identifier that identifies the        message 400.    -   message text payload 404: text, to be generated by a user via a        user interface of the client device 102, and that is included in        the message 400.    -   message image payload 406: image data, captured by a camera        component of a client device 102 or retrieved from a memory        component of a client device 102, and that is included in the        message 400. Image data for a sent or received message 400 may        be stored in the image table 312.    -   message video payload 408: video data, captured by a camera        component or retrieved from a memory component of the client        device 102, and that is included in the message 400. Video data        for a sent or received message 400 may be stored in the video        table 304.    -   message audio payload 410: audio data, captured by a microphone        or retrieved from a memory component of the client device 102,        and that is included in the message 400.    -   message augmentation data 412: augmentation data (e.g., filters,        stickers, or other annotations or enhancements) that represents        augmentations to be applied to message image payload 406,        message video payload 408, or message audio payload 410 of the        message 400. Augmentation data for a sent or received message        400 may be stored in the augmentation table 310.    -   message duration parameter 414: parameter value indicating, in        seconds, the amount of time for which content of the message        (e.g., the message image payload 406, message video payload 408,        message audio payload 410) is to be presented or made accessible        to a user via the messaging client 104.    -   message geolocation parameter 416: geolocation data (e.g.,        latitudinal and longitudinal coordinates) associated with the        content payload of the message. Multiple message geolocation        parameter 416 values may be included in the payload, each of        these parameter values being associated with respect to content        items included in the content (e.g., a specific image within the        message image payload 406, or a specific video in the message        video payload 408).    -   message story identifier 418: identifier values identifying one        or more content collections (e.g., “stories” identified in the        story table 314) with which a particular content item in the        message image payload 406 of the message 400 is associated. For        example, multiple images within the message image payload 406        may each be associated with multiple content collections using        identifier values.    -   message tag 420: each message 400 may be tagged with multiple        tags, each of which is indicative of the subject matter of        content included in the message payload. For example, where a        particular image included in the message image payload 406        depicts an animal (e.g., a lion), a tag value may be included        within the message tag 420 that is indicative of the relevant        animal. Tag values may be generated manually, based on user        input, or may be automatically generated using, for example,        image recognition.    -   message sender identifier 422: an identifier (e.g., a messaging        system identifier, email address, or device identifier)        indicative of a user of the client device 102 on which the        message 400 was generated and from which the message 400 was        sent.    -   message receiver identifier 424: an identifier (e.g., a        messaging system identifier, email address, or device        identifier) indicative of a user of the client device 102 to        which the message 400 is addressed.

The contents (e.g., values) of the various components of message 400 maybe pointers to locations in tables within which content data values arestored. For example, an image value in the message image payload 406 maybe a pointer to (or address of) a location within an image table 312.Similarly, values within the message video payload 408 may point to datastored within a video table 304, values stored within the messageaugmentation data 412 may point to data stored in an augmentation table310, values stored within the message story identifier 418 may point todata stored in a story table 314, and values stored within the messagesender identifier 422 and the message receiver identifier 424 may pointto user records stored within an entity table 306.

External Mesh Deformation System

FIG. 5 is a block diagram showing an example external mesh deformationsystem 224, according to example examples. External mesh deformationsystem 224 includes a set of components 510 that operate on a set ofinput data (e.g., a monocular image depicting a real-world object, suchas a person or training data). The set of input data is obtained fromone or more database(s) (FIG. 3 ) during the training phases and isobtained from an RGB camera of a client device 102 when an AR/VRapplication is being used, such as by a messaging client 104. Externalmesh deformation system 224 includes a machine learning technique module512, a skeletal key-points module 511, a body mesh module 514, an imagemodification module 518, an AR effect module 519, an external meshmodule 530, a deformation model selection module 532, a 3D body trackingmodule 513, a whole-body segmentation module 515, and an image displaymodule 520.

During training, the external mesh deformation system 224 receives agiven training image or video from training data 501. The external meshdeformation system 224 applies one or more machine learning techniquesusing the machine learning technique module 512 on the given trainingimage or video. The machine learning technique module 512 extracts oneor more features from the given training image or video to estimate a 3Dbody mesh of the person(s) or user(s) depicted in the image or video.

The machine learning technique module 512 retrieves 3D body meshinformation associated with the given training image or video. Themachine learning technique module 512 compares the estimated 3D bodymesh with the ground truth garment 3D body mesh provided as part of thetraining data 502. Based on a difference threshold or deviation of thecomparison, the machine learning technique module 512 updates one ormore coefficients or parameters and obtains one or more additionaltraining images or videos. After a specified number of epochs or batchesof training images have been processed and/or when the differencethreshold or deviation reaches a specified value, the machine learningtechnique module 512 completes training and the parameters andcoefficients of the machine learning technique module 512 are stored inthe trained machine learning technique(s) 307.

In some examples, during training, the machine learning technique module512 receives 2D skeletal joint information from a skeletal key-pointsmodule 511. The skeletal key-points module 511 tracks skeletal keypoints of a user depicted in a given training image (e.g., head joint,shoulder joints, hip joints, leg joints, and so forth) and provides the2D or 3D coordinates of the skeletal key points. This information isused by the machine learning technique module 512 to identifydistinguishing attributes of the user depicted in the training image andto generate the 3D body mesh.

The 3D body mesh generated by the machine learning technique module 512is provided to the body mesh module 514. The body mesh module 514 cantrack the object depicted in the image or video and update the 3D bodymesh associated with the object. In an example, the body mesh module 514can track the object based on 3D body tracking information provided bythe 3D body tracking module 513. The body mesh module 514 can update the3D body mesh in 3D and can adjust a position, body type, rotation, orany other parameter of the 3D body mesh.

FIG. 6 is a diagrammatic representation of outputs of the external meshdeformation system 224, in accordance with some examples. Specifically,FIG. 6 shows a 3D body mesh 600 generated and tracked by the body meshmodule 514. In one example, the body mesh module 514 can track changesof the 3D body mesh across frames of the video. The body mesh module 514can provide changes to the 3D body mesh to the external mesh module 530to update and deform one or more portions of the external mesh that areassociated with deformation attributes corresponding to a body movementdeformation model. As an example, the one or more portions can beattached to or overlap the 3D body mesh and can be adjusted or deformedbased on changes to the 3D body mesh.

The external mesh module 530 can identify different portions of theexternal mesh to deform based on respective deformation attributes. Forexample, a first deformation attribute can correspond to a garmentlocation metric. The garment location metric can be used to associate aparticular set of portions of the external mesh with a given deformationmodel based on the location of the particular set of portions relativeto one or more landmarks of the 3D body mesh. Specifically, the garmentlocation metric can identify a landmark on the 3D body mesh, such as alegs region, a torso region, or head region of the 3D body mesh. Thegarment location metric can also specify a minimum or maximum distanceaway from the identified landmark. The external mesh module 530 candetermine a set of vertices of the external mesh that correspond to thegarment location metric based on how the set of vertices are initiallyplaced or aligned or correspond to the 3D body mesh.

In one example, the garment location metric can identify the legs regionas the specified landmark of the 3D body mesh. In such cases, theexternal mesh module 530 can determine that a first set of vertices or afirst portion of the external mesh overlaps the legs region of the 3Dbody mesh. In response, the external mesh module 530 can determine thatthe garment location metric for the first set of vertices or the firstportion of the external mesh satisfies the garment location metric. Theexternal mesh module 530 can then communicate with the deformation modelselection module 532 to obtain and apply a first deformation model tothe first set of vertices or the first portion of the external mesh. Thedeformation model selection module 532 can identify the firstdeformation model that is associated with satisfaction of the garmentlocation metric. The deformation model selection module 532 can thenapply the first deformation model (e.g., an external force model) to thefirst set of vertices or the first portion of the external mesh.

The external mesh module 530 can determine that a second set of verticesor a second portion of the external mesh is placed more than a thresholddistance away from the specified landmark, such as the legs region ofthe 3D body mesh. In response, the external mesh module 530 candetermine that the garment location metric for the second set ofvertices or the second portion of the external mesh fails to satisfy thegarment location metric. The external mesh module 530 can thencommunicate with the deformation model selection module 532 to obtainand apply a second deformation model to the second set of vertices orthe second portion of the external mesh corresponding to a portion thatfails to satisfy the garment location metric. The deformation modelselection module 532 can identify the second deformation model that isassociated with failure to satisfy the garment location metric. Thedeformation model selection module 532 can then apply the seconddeformation model (e.g., a body movement model) to the second set ofvertices or the second portion of the external mesh.

The external mesh module 530 can determine that a third set of verticesor a third portion of the external mesh is placed more than a thresholddistance away from another landmark, such as the torso region of the 3Dbody mesh. In response, the external mesh module 530 can determine thatthe garment location metric for the third set of vertices or the thirdportion of the external mesh satisfies the garment location metric. Theexternal mesh module 530 can then communicate with the deformation modelselection module 532 to obtain and apply a third deformation model tothe third set of vertices or the third portion of the external mesh. Thedeformation model selection module 532 can identify the thirddeformation model that is associated with the garment location metric.The deformation model selection module 532 can then apply the thirddeformation model (e.g., a cloth simulation model) to the third set ofvertices or the third portion of the external mesh.

The portions identified by the external mesh module 530 can change overtime to be associated with different deformation models as thereal-world object associated with the external mesh moves in a video.Namely, at a first point in time, the first portion of the external meshcan be determined to satisfy the first deformation attribute. In suchcases, the first portion can be deformed based on the first deformationmodel. Later, at a second point in time, the real-world object can moveor rotate resulting in movement of the external mesh. As a result, thefirst portion can now be determined to no longer satisfy the firstdeformation attribute and, in response, the first portion can, at thesecond point in time, be deformed based on the second deformation modelinstead of the first deformation model.

In some cases, the different deformation attributes can be ranked orweighted to control how much and what type of deformation to apply tothe corresponding region of the external mesh. Namely, in someimplementations, the deformation model selection module 532 candetermine that the same set of vertices or the first portion of theexternal mesh is associated with and satisfies multiple deformationattributes. In such cases, the deformation model selection module 532can determine a ranking of the deformation attributes and only apply onedeformation model to the set of vertices or the first portion that isassociated with a highest rank. In some implementations, the deformationmodel selection module 532 can obtain weights associated with themultiple deformation attributes that are satisfied or associated withthe set of vertices or the first portion of the external mesh. Thedeformation model selection module 532 can then apply multipledeformation models to the set of vertices or the first portion of theexternal mesh in a blended manner, such that the amount of deformationapplied by each deformation model corresponds to the weight associatedwith the corresponding deformation attribute. For example, the set ofvertices or the first portion of the external mesh can be associatedwith first and second deformation attributes where the first deformationattribute is associated with a weight of 0.3 and the second deformationattribute is associated with a weight of 0.7. In such cases, thedeformation model selection module 532 can apply a first deformationmodel associated with the first deformation attribute to the set ofvertices or the first portion of the external mesh in a blended mannerwith a second deformation model associated with the second deformationattribute. Namely, the deformation model selection module 532 can deformthe set of vertices or the first portion by an amount of 0.3 based onthe first deformation model and by an amount of 0.7 based on the seconddeformation model.

As another example, a second deformation attribute can correspond to agarment looseness metric. The garment looseness metric can be used toassociate a particular set of portions of the external mesh with a givendeformation model based on how loose particular set of portions are.Specifically, the garment looseness metric can identify the looseness ofa particular region or each region of the garment.

In one example, the garment looseness metric can identify a first set ofvertices or a first portion of the external mesh that is associated witha first looseness. The external mesh module 530 can determine inresponse that the garment looseness metric is satisfied for the firstportion of the external mesh based on the first looseness. The externalmesh module 530 can then communicate with the deformation modelselection module 532 to obtain and apply a first deformation model tothe first portion of the external mesh. The deformation model selectionmodule 532 can identify the first deformation model that is associatedwith satisfaction of the garment looseness metric. The deformation modelselection module 532 can then apply the first deformation model (e.g.,an external force model) to the first portion of the external mesh.Similarly, the external mesh module 530 can determine that a secondportion of the external mesh is associated with a second looseness. Inresponse, the external mesh module 530 can determine that the garmentlooseness metric is not satisfied for the second portion. The externalmesh module 530 can then communicate with the deformation modelselection module 532 to obtain and apply a second deformation model tothe second portion of the external mesh corresponding to a portion thatfails to satisfy the garment looseness metric. The deformation modelselection module 532 can identify the second deformation model that isassociated with failure to satisfy the garment looseness metric. Thedeformation model selection module 532 can then apply the seconddeformation model (e.g., a body movement model) to the second portion ofthe external mesh.

For example, a third deformation attribute can correspond to a body meshdensity threshold. The garment location metric can be used to associatea particular set of portions of the external mesh with a givendeformation model based on the body density of one or more landmarks ofthe 3D body mesh. The body density can be computed by obtaining a weightof the real-world object depicted in the image or video associated withthe 3D body mesh and dividing the weight by a quantity of pixels in agiven region. A greater density represents a smaller value resultingfrom diving the weight by the quantity of pixels in the given regionwhereas a smaller density represents a larger value resulting fromdiving the weight by the quantity of pixels in the given region. Theexternal mesh module 530 can determine a set of vertices of the externalmesh that correspond to the body mesh density threshold based oncomputing a density of the pixels in a first region based on the weightof the real-world object. The external mesh module 530 can identify afirst portion that has a density that is lower than the body meshdensity threshold (e.g., the first portion satisfies the body meshdensity threshold) and a second portion that has a density that isgreater than the body mesh density threshold (e.g., the second portionexceeds the body mesh density threshold).

The external mesh module 530 can then communicate with the deformationmodel selection module 532 to obtain and apply a first deformation modelto the first portion of the external mesh and a second deformation modelto the second portion. The deformation model selection module 532 canidentify the first deformation model that is associated withsatisfaction of the body mesh density threshold and can identify asecond deformation model that is associated with exceeding the body meshdensity threshold. The deformation model selection module 532 can thenapply the first deformation model to the first portion of the externalmesh and the second deformation model to the second portion of theexternal mesh.

For example, a fourth deformation attribute can correspond to a distancethreshold. The distance threshold can be used to associate a particularset of portions of the external mesh with a given deformation modelbased on the distance of such portions relative to different portions ofthe 3D body mesh. In an example, the external mesh module 530 canidentify a first portion of the external mesh that has a vertex that ismore than a threshold distance away from an edge of the corresponding 3Dbody mesh. For example, the external mesh module 530 can select a vertexof the external mesh that corresponds to a legs portion of the 3D bodymesh. The external mesh module 530 can compute a distance between thevertex or set of vertices of the external mesh that correspond to thelegs portion and an edge or set of edges of the legs portion. Theexternal mesh module 530 can compare the computed distance to thedistance threshold to determine if the distance threshold is satisfiedor fails to be satisfied. In such cases where the distance is more thanthe distance threshold, the external mesh module 530 can determine thatthe first portion fails to satisfy the distance threshold. The externalmesh module 530 can then communicate with the deformation modelselection module 532 to obtain and apply a first deformation model tothe first portion of the external mesh.

As another example, a fifth deformation attribute can correspond to auser-labeled vertex attributes. The user-labeled vertex attributes canbe used to associate a particular set of portions of the external meshwith a given deformation model based on labels a creator of the externalmesh attached to the vertices of the external mesh. Specifically, thecreator of the external mesh can attach or associate an identifier, suchas a number or a color, to an attribute of a vertex or set of verticesof the external mesh. The external mesh module 530 can detect thisidentifier and use the identifier to select a particular deformationmodel to apply to the vertex or set of vertices.

In another example, the external mesh module 530 can identify a secondportion of the external mesh that has a vertex that is less than athreshold distance away from an edge of the corresponding 3D body mesh.For example, the external mesh module 530 can select a vertex of theexternal mesh that corresponds to a torso portion of the 3D body mesh.The external mesh module 530 can compute a distance between the vertexor set of vertices of the external mesh that correspond to the torsoportion and an edge or set of edges of the torso portion. The externalmesh module 530 can compare the computed distance to the distancethreshold to determine if the distance threshold is satisfied or failsto be satisfied. In such cases where the distance is less than thedistance threshold, the external mesh module 530 can determine that thesecond portion satisfies the distance threshold. The external meshmodule 530 can then communicate with the deformation model selectionmodule 532 to obtain and apply a second deformation model to the secondportion of the external mesh.

In one example, the deformation model that is applied to a given portionof the external mesh is a body movement model. In such cases, theexternal mesh module 530 can provide movement information of the 3D bodymesh to the deformation model selection module 532. The deformationmodel selection module 532 can deform the identified portion of theexternal mesh (separately from the other portion(s)) based on thedeformation or movement information of the 3D body mesh. For example,the external mesh module 530 can receive indication of a direction ofmovement or displacement, a rotation, or an adjustment to a shape, size,or position of the 3D body mesh and can then deform the identifiedportion of the external mesh based on the received indication in suchcases where the identified portion is associated with a movementdeformation model.

In an example, the body mesh module 514 can determine a first set ofcoordinates of the 3D body mesh in a normal-tangent space for a firstframe of the frames of the video and can determine a second set ofcoordinates of the 3D body mesh in the normal-tangent space for a secondframe of the frames of the video. The body mesh module 514 can compute,in real time, a change between the first and second sets of coordinatesin the normal-tangent space and can transfer the change between thefirst and second sets of coordinates in the normal-tangent space to theexternal mesh. Specifically, the external mesh module 530 can update andadjust a 3D position and a 3D orientation of the external mesh portionthat is associated with a body movement deformation model based on thechange between the first and second sets of coordinates in thenormal-tangent space. In this way, the external mesh module 530 candeform the portion(s) of the external mesh associated with an AR graphicwithout using a rig or bone information of the real-world object.

In an example, the external mesh module 530 can compute a rate at whichthe first set of coordinates changes to the second set of coordinates inthe normal-tangent space (or any other suitable space). The externalmesh module 530 can deform the other portion(s) of the external meshbased on an external force model representing the rate at which thefirst set of coordinates changes to the second set of coordinates in thenormal-tangent space (or any other suitable space). For example, if theperson depicted in the image or video turns or twists at a particularrate or speed, the body mesh module 514 can compute a first rate thatrepresents the direction and the speed at which the person turns ortwists. This first rate is provided to the external mesh module 530which then changes or deforms the free hanging or dangling portion ofthe external mesh based on the first rate. In an example, the first ratecan include a first value, in which case, the second portion of theexternal mesh is moved along a z-axis in an opposite direction from thedirection at which the person turns or twists at the same speed as theperson turns or twists.

The external mesh module 530 can receive an indication of an AR graphicfrom the AR effect module 519. The AR effect module 519 can receive auser input that selects a given AR graphic (e.g., an AR purse, ARnecklace, AR cloth arm band, AR belt, and so forth) to add in real timeto an underlying image or video. The external mesh module 530 can accessa database and search the database for an external mesh associated withthe given AR graphic. The external mesh module 530 can obtain placementinformation for the external mesh. The placement information can specifywhere to place the AR graphic in the image or video in relation to orrelative to the real-world object and which portions of the AR graphicare deformed based on which type of deformation model (e.g., based onmovement of the real-world object or based on external force simulation(e.g., wind, collision, physics, gravity, and so forth)).

In one example, the placement information can specify an edge or bodypart of the 3D body mesh corresponding to the real-world graphic (e.g.,a left arm, a right arm, a head, and so forth) that is attached to oroverlaps the first portion(s) of the external mesh. The placementinformation can also specify a minimum distance between the edge or bodypart away from which an edge of the corresponding AR graphic (firstportion(s) of the external mesh) can be rendered for display. Inresponse, the external mesh module 530 can maintain the position of theexternal mesh (and corresponding AR graphic) throughout a plurality ofvideo frames at least the minimum distance away from the edge or bodypart of the body mesh. At the same time, a second portion of theexternal mesh is moved, displaced, and deformed based on outputs of thedeformation model selection module 532.

In one example, the placement information can specify an edge or bodypart of the body mesh corresponding to the real-world graphic (e.g., aleft arm, a right arm, a head, and so forth) that is attached to oroverlaps the first portion(s) of the external mesh. The placementinformation can also specify a maximum distance between the edge or bodypart away from which an edge of the corresponding AR graphic (externalmesh) can be rendered for display. In response, the external mesh module530 can maintain the position of the external mesh (and corresponding ARgraphic) throughout a plurality of video frames, at most the maximumdistance away from the edge or body part of the body mesh. At the sametime, a second portion of the external mesh is moved, displaced, anddeformed based on outputs of the deformation model selection module 532.

In one example, the placement information can specify an edge or bodypart of the body mesh corresponding to the real-world graphic (e.g., aleft arm, a right arm, a head, and so forth) that is attached to oroverlaps the first portion(s) of the external mesh. The placementinformation can also specify a range of distances between the edge orbody part away from which an edge of the corresponding AR graphic(external mesh) can be rendered for display. In response, the externalmesh module 530 can maintain the position of the external mesh (andcorresponding AR graphic) throughout a plurality of video frames betweenminimum and maximum values of the range of distances away from the edgeor body part of the body mesh. At the same time, a second portion of theexternal mesh is moved, displaced, and deformed based on outputs of thedeformation model selection module 532.

In one example, the placement information can specify relative UVchannel coordinates of the 3D body mesh that is attached to or overlapsthe first portion(s) of the external mesh. The relative UV channelcoordinates can be used to maintain and place the external mesh (andcorresponding AR graphic) within the image or video depicting an object.In this case, the external mesh module 530 can obtain UV channelcoordinates of the 3D body mesh corresponding to the real-world objectdepicted in the image or video. The external mesh module 530 can alsocompute a set of UV channel coordinates of the first portion(s) of theexternal mesh based on the UV coordinates associated with the 3D bodymesh and the relative UV channel coordinates in the placementinformation. For example, the placement information can specify aminimum or maximum distance away from a particular UV channel coordinateof the 3D body mesh at which the first portion(s) of the external meshcan be placed. In response, the external mesh module 530 can place theexternal mesh at a set of UV channel coordinates that are within theminimum or maximum distances from the UV coordinates of the 3D bodymesh. As a result, the corresponding AR graphic associated with theexternal mesh is added to the image or video at the position thatcorresponds to the set of UV coordinates. At the same time, a secondportion of the external mesh is moved, displaced, and deformed based onoutputs of the deformation model selection module 532. Namely, theexternal mesh module 530 can identify a second portion(s) of theexternal mesh that is attached to the first portion(s) or adjacent tothe first portion(s) of the external mesh and that is not attached tothe 3D body mesh. This second portion(s) can be deformed and moved basedon information received from the deformation model selection module 532.

The placement information can specify which vertices, pixels, UVcoordinates, or locations of the external mesh are associated with,attached to, and/or overlap the 3D body mesh. The placement informationcan specify which vertices, pixels, UV coordinates, or locations of theexternal mesh dangle freely from the 3D body mesh. For these secondportions, the placement information includes an instruction to deformthe external mesh based on computations and deformations provided by thedeformation model selection module 532. In one example, the placementinformation can include external force details that specify an externalforce function(s) to use to compute the corresponding deformation of thesecond portions. The external force function can include a physicssimulation, a collision simulation, chain physics, a cloth simulation,and/or other suitable external force simulation functions.

Based on the placement information and changes detected for the 3D bodymesh, the external mesh module 530 can deform the first portion(s) ofthe external mesh in correspondence to the changes detected in the 3Dbody mesh. In one example, the external mesh can be deformed to changethe position in 3D relative to the 3D body mesh in response to detectinga change in 3D position of the 3D body mesh. For example, if the 3D bodymesh is determined to move along a first axis by a first amount, theexternal mesh is similarly moved along the first axis by the firstamount (or some other amount that is computed as a factor of the firstamount). A second portion of the external mesh can be moved along asecond axis based on external force simulation information received fromthe deformation model selection module 532. As another example, theexternal mesh can be rotated or twisted in a corresponding manner to the3D body mesh. Specifically, if the 3D body mesh is determined to rotatealong a rotational axis by a second amount, the external mesh issimilarly rotated along the rotational axis by the second amount (orsome other amount that is computed as a factor of the second amount).

As another example, the first portion(s) of the external mesh can bedeformed based on changes to the body shape, body state, or bodyproperties across frames of the image or video without deforming thesecond portion(s) of the external mesh. Specifically, if a portion ofthe 3D body mesh is reduced in size (e.g., a waist is indented by aspecified amount as a result of an external force, such as a hand beingplaced on the waist), the corresponding portion of the external mesh isalso reduced in size or repositioned in 3D space by the same amount orother specified amount. Namely, if the external mesh is associated withan AR purse strap that is overlaid on top of the person depicted in theimage or video, the AR strap of the purse (the portion of the externalmesh associated with the AR strap of the purse corresponding to thewaist) is reduced in size or indented as a result of the 3D body meshbeing reduced in size or being indented. In another example, the 3D bodymesh can periodically expand and contract a chest portion of the 3D bodymesh (or upper body portion) based on a breathing cycle of the persondepicted in the image. In such cases, the corresponding portion of theexternal mesh that is placed over the chest or upper body portion of the3D body mesh (but not any other portion of the external mesh) isdeformed to expand and contract in size in correspondence with thebreathing cycle.

In an example, the body mesh module 514 can compute changes in theNormal-Tangent space of the corresponding object. Namely, the body meshmodule 514 can determine movement of the 3D body mesh in theNormal-Tangent space and can provide indications of that movement to theexternal mesh module 530. The external mesh module 530 can apply changesto the external mesh based on the movement in the Normal-Tangent space.In some cases, the external mesh module 530 can deform the firstportion(s) of the external mesh to mirror the same movement in theNormal-Tangent space. In some cases, the external mesh module 530 candeform the first portion(s) of the external mesh as a factor of themovement in the Normal-Tangent space. At the same time, the externalmesh module 530 can deform the second portion(s) of the external meshbased on a rate of the changes in the Normal-Tangent space of thecorresponding object. Namely, the first portion(s) of the external meshcan be deformed to mirror the changes in the Normal-Tangent space of the3D body mesh while the second portion(s) of the external mesh can bedeformed as a function of a rate at which such changes occur.

The deformation model selection module 532 can implement a plurality ofdifferent deformation models, including one or more external forcesimulation models, and can combine their outputs to generate movementand deformation information for the respective portion(s) of theexternal mesh. For example, the deformation model selection module 532can implement a gravity force simulation model that computes a newtrajectory for a corresponding portion of the external mesh (e.g., aportion of the external mesh determined to have a deformation attributeassociated with a gravity force simulation deformation model) based onmotion information associated with a given object depicted in an imageor video. The gravity force simulation model receives as input a currentposition of an object, past position of the object, movement vectors ofthe object, orientation of the object, a position of the secondportion(s) of the external mesh when the object was at the pastposition, and a directional gravity function. The gravity forcesimulation model outputs a new set of coordinates and positions for thesecond portion(s) of the external mesh corresponding to the currentposition of the object based on application of the directional gravityfunction to the current position of an object, past position of theobject, movement vectors of the object, orientation of the object, or aposition of the second portion(s) of the external mesh when the objectwas at the past position. The new set of coordinates and positions ofthe second portion(s) of the external mesh are provided to the externalmesh module 530, which then deforms the corresponding portion(s) basedon the previous positions, the new set of coordinates and positions ofthe second portion(s) of the external mesh, and the relative position ofthe 3D body mesh.

As another example, the deformation model selection module 532 canimplement a cloth simulation model that computes a new trajectory for acorresponding portion of the external mesh (e.g., a portion of theexternal mesh determined to have a deformation attribute associated witha cloth simulation deformation model) based on motion informationassociated with a given object depicted in an image or video and a clothor material type associated with the AR element corresponding to theexternal mesh. The cloth simulation model receives as input a currentposition of an object, past position of the object, movement vectors ofthe object, orientation of the object, a position of the correspondingportion(s) of the external mesh when the object was at the pastposition, a material or cloth type associated with the correspondingportion(s) of the external mesh, and a cloth simulation function. Thecloth simulation model outputs a new set of coordinates and positionsfor the corresponding portion(s) of the external mesh corresponding tothe current position of the object based on application of the clothsimulation function to the current position of an object, past positionof the object, movement vectors of the object, orientation of theobject, cloth or material type of the corresponding portion(s), or aposition of the second portion(s) of the external mesh when the objectwas at the past position. The new set of coordinates and positions ofthe corresponding portion(s) of the external mesh are provided to theexternal mesh module 530, which then deforms the correspondingportion(s) based on the previous positions, the new set of coordinatesand positions of the second portion(s) of the external mesh, the clothor material type, and the relative position of the 3D body mesh.

As another example, the deformation model selection module 532 canimplement a chain physics simulation model that computes a newtrajectory for a corresponding portion of the external mesh (e.g., aportion of the external mesh determined to have a deformation attributeassociated with a chain physics simulation deformation model) based onmotion information associated with a given object depicted in an imageor video. The chain physics simulation model receives as input a currentposition of an object, past position of the object, movement vectors ofthe object, orientation of the object, a position of the correspondingportion(s) of the external mesh when the object was at the pastposition, and a chain physics function. The chain physics simulationmodel outputs a new set of coordinates and positions for thecorresponding portion(s) of the external mesh corresponding to thecurrent position of the object based on application of the chain physicsfunction to the current position of an object, past position of theobject, movement vectors of the object, orientation of the object, or aposition of the second portion(s) of the external mesh when the objectwas at the past position. The new set of coordinates and positions ofthe corresponding portion(s) of the external mesh are provided to theexternal mesh module 530, which then deforms the correspondingportion(s) based on the previous positions, the new set of coordinatesand positions of the second portion(s) of the external mesh, and therelative position of the 3D body mesh.

As another example, the deformation model selection module 532 canimplement a collision simulation model that computes a new trajectoryfor a corresponding portion of the external mesh (e.g., a portion of theexternal mesh determined to have a deformation attribute associated witha collision simulation deformation model) based on motion informationassociated with a given object depicted in an image or video. Thecollision simulation model receives as input a current position of anobject, past position of the object, movement vectors of the object,orientation of the object, a position of the corresponding portion(s) ofthe external mesh when the object was at the past position, and acollision function. The collision simulation model outputs an amount ofexpansion or contraction for the corresponding portion(s) of theexternal mesh corresponding to the current position of the object basedon application of the collision function to the current position of anobject, past position of the object, movement vectors of the object,orientation of the object, or a position of the corresponding portion(s)of the external mesh when the object was at the past position. Forexample, if the corresponding portion(s) of the external mesh isdetermined by the collision simulation model to collide or overlap withan edge of the object at a first rate, the amount of expansion orcontraction is computed to be a first value. The first value can also bea factor of the material or type of the AR element represented by theexternal mesh and/or the material or type of the object. If thecorresponding portion(s) of the external mesh is determined by thecollision simulation model to collide or overlap with an edge of theobject at a second rate (greater than the first rate), the amount ofexpansion or contraction is computed to be a second value that isgreater than the first value. The amount of expansion or contraction ofthe corresponding portion(s) of the external mesh are provided to theexternal mesh module 530, which then deforms the correspondingportion(s) based on the previous positions, the new set of coordinatesand positions of the corresponding portion(s) of the external mesh, andthe relative position of the 3D body mesh and the amount of expansion orcontraction. In this way, one portion of the external mesh can beexpanded or contracted based on a collision simulation, while the otherportion of the external mesh is only deformed based on movement of the3D body mesh and may not necessarily be expanded or contracted.

In an example, the AR effect selection module 519 selects and appliesone or more AR elements or graphics to an object depicted in the imageor video based on the body mesh associated with the object received fromthe body mesh module 514. These AR graphics combined with the real-worldobject depicted in the image or video are provided to the imagemodification module 518 to render an image or video that depicts theperson wearing the AR object, such as an AR purse or earrings.

The image modification module 518 can adjust the image captured by thecamera based on the AR effect selected by the visual effect selectionmodule 519. The image modification module 518 adjusts the way in whichthe AR garment(s) or fashion accessory placed over the user or persondepicted in the image or video is/are presented in an image or video,such as by changing the physical properties (deformation) of the ARgarment or fashion accessory based on the changes to the 3D body mesh ofthe user and an external force simulation and applying one or more ARelements (AR graphical elements). Image display module 520 combines theadjustments made by the image modification module 518 into the receivedmonocular image or video depicting the user's body. The image or videois provided by the image display module 520 to the client device 102 andcan then be sent to another user or stored for later access and display.

In some examples, the image modification module 518 and/or the externalmesh module 530 receive 3D body tracking information representing the 3Dpositions of the user depicted in the image from the 3D body trackingmodule 513. The 3D body tracking module 513 generates the 3D bodytracking information by processing the training data 501 usingadditional machine learning techniques. The image modification module518 can also receive a whole-body segmentation representing which pixelsin the image correspond to the whole body of the user from anothermachine learning technique. The whole-body segmentation can be receivedfrom the whole-body segmentation module 515. The whole-body segmentationmodule 515 generates the whole-body segmentation by processing thetraining data 501 using a machine learning technique.

In one example, as shown in FIG. 7 , the AR effect selection module 519can apply one or more AR effects to an object depicted in an image orvideo 700 corresponding to a 3D body mesh 710 captured by a clientdevice 102 using an external mesh 720. The external mesh 720 can includea first portion 750 that is associated with a first deformationattribute and a second portion 752 that is associated with a seconddeformation attribute. In an example, the first portion 750 can includea part of a dress that is fit tight around a torso of a person and thesecond portion 752 can include a bottom of the dress that fits looselyaround the legs of the person.

The external mesh module 530 can receive the 3D body mesh 710 and canalso obtain the external mesh 720, such as from a storage device,associated with an AR graphic 730 (e.g., an AR dress). The external meshmodule 530 can obtain placement information 740 associated with theexternal mesh 720. The placement information 740 can specify proximityparameters 742, UV channel coordinates 744, and/or deformationattributes 746. Based on the placement information 740, the externalmesh module 530 can specify where to place and position the externalmesh 720 (and the corresponding AR graphic 730) in the image or video700. Based on the placement information 740, the external mesh module530 can identify different portions of the AR graphic 730 (e.g., thefirst portion 750 that satisfies one or more deformation attributes anda second portion 752 that satisfies one or more other deformationattributes) and instruct the deformation model selection module 532 toapply different deformation models to the different portions of the ARgraphic 730.

In an example, the external mesh module 530 can compute a correspondence722 between the first portion 750 of the external mesh 720 and the 3Dbody mesh 710. The correspondence 722 can be used to deform the firstportion 750 of the external mesh 720 in 3D along one or more axes 724based on how the 3D body mesh 710 is deformed (e.g., based on a movementmodel). As the external mesh module 530 deforms the first portion 750 ofthe external mesh 720, the corresponding AR graphic 730 is similarlydeformed and rendered for display within the image or video based on theplacement information 740. The external mesh module 530 can obtaindeformation information for the second portion 752 and can deform thesecond portion 752 (independently of, separate from, and/or togetherwith) the first portion 750 based on an external force deformationmodel.

In one example, to generate the placement information 740, an AR graphicdesigner can be provided on a client device 102 with a reference 3D bodymesh. The AR graphic designer can drag and drop the external mesh (e.g.,external mesh 720), on the reference 3D body mesh, that the graphicdesigner creates in association with an AR graphic. The AR graphicdesigner can input relative placement parameters, such as proximityparameters and UV channel coordinates, or the client device 102 canautomatically compute the placement parameters based on how close andhow far different edges or pixels of the external mesh are with respectto different edges, pixels, or body parts of the 3D body mesh. Usingthis information, the placement information 740 is generated and storedin association with the AR graphic. In some cases, the placementinformation 740 is automatically created and presented to the ARdesigner. The AR designer can specify a range, a minimum value, ormaximum value for each edge or one or more edges or pixels or voxels ofthe external mesh. These ranges, minimum values, or maximum values areused by the external mesh module 530 to control placement andpositioning of the external mesh (and corresponding AR graphic) withinan image or video based on the 3D body mesh of an object depicted in theimage or video.

The AR graphic designer can also be provided a graphical user interfacefor inputting the deformation attributes 746. The AR graphic designercan also specify UV coordinates, voxel positions, placement positions,and/or coordinates of the deformation attributes 746. The AR graphicdesigner can input custom deformation functions, such as external forcefunctions and/or can select a subset of external force functions toapply.

As shown in FIG. 8 , after the external mesh is deformed based ondeformation information and movement of the 3D body mesh 710, thecorresponding AR graphic 730 is rendered for display on the image orvideo. Specifically, the image or video 800 includes a depiction of theuser or person 810 and the AR graphic 730 (e.g., AR dress) that has beendeformed based on movement of the 3D body mesh. The image or video 800includes a depiction of the user or person 810 and deformed AR graphic822 (e.g., AR dress) that has been deformed based on computations of theexternal force provided by the deformation model selection module 532.

FIG. 9 is a flowchart of a process 900 performed by the external meshdeformation system 224, in accordance with some examples. Although theflowchart can describe the operations as a sequential process, many ofthe operations can be performed in parallel or concurrently. Inaddition, the order of the operations may be re-arranged. A process isterminated when its operations are completed. A process may correspondto a method, a procedure, and the like. The steps of methods may beperformed in whole or in part, may be performed in conjunction with someor all of the steps in other methods, and may be performed by any numberof different systems or any portion thereof, such as a processorincluded in any of the systems.

At operation 901, the external mesh deformation system 224 (e.g., aclient device 102 or a server) receives a video that includes adepiction of a real-world object, as discussed above.

At operation 902, the external mesh deformation system 224 generates a3D body mesh associated with the real-world object that tracks movementof the real-world object across frames of the video, as discussed above.

At operation 903, the external mesh deformation system 224 obtains anexternal mesh associated with an AR element, as discussed above.

At operation 904, the external mesh deformation system 224 accesses aplurality of deformation attributes associated with the external mesh,each of the plurality of deformation attributes corresponding to adifferent deformation model, as discussed above.

At operation 905, the external mesh deformation system 224 separatelydeforms, based on respective deformation models, a first portion of theexternal mesh associated with a first of the plurality of deformationattributes and a second portion of the external mesh associated with asecond of the plurality of deformation attributes, as discussed above.

At operation 906, the external mesh deformation system 224 modifies thevideo to include a display of the AR element based on the separatelydeformed first and second portions of the external mesh, as discussedabove.

Machine Architecture

FIG. 10 is a diagrammatic representation of the machine 1000 withinwhich instructions 1008 (e.g., software, a program, an application, anapplet, an app, or other executable code) for causing the machine 1000to perform any one or more of the methodologies discussed herein may beexecuted. For example, the instructions 1008 may cause the machine 1000to execute any one or more of the methods described herein. Theinstructions 1008 transform the general, non-programmed machine 1000into a particular machine 1000 programmed to carry out the described andillustrated functions in the manner described. The machine 1000 mayoperate as a standalone device or may be coupled (e.g., networked) toother machines. In a networked deployment, the machine 1000 may operatein the capacity of a server machine or a client machine in aserver-client network environment, or as a peer machine in apeer-to-peer (or distributed) network environment. The machine 1000 maycomprise, but not be limited to, a server computer, a client computer, apersonal computer (PC), a tablet computer, a laptop computer, a netbook,a set-top box (STB), a personal digital assistant (PDA), anentertainment media system, a cellular telephone, a smartphone, a mobiledevice, a wearable device (e.g., a smartwatch), a smart home device(e.g., a smart appliance), other smart devices, a web appliance, anetwork router, a network switch, a network bridge, or any machinecapable of executing the instructions 1008, sequentially or otherwise,that specify actions to be taken by the machine 1000. Further, whileonly a single machine 1000 is illustrated, the term “machine” shall alsobe taken to include a collection of machines that individually orjointly execute the instructions 1008 to perform any one or more of themethodologies discussed herein. The machine 1000, for example, maycomprise the client device 102 or any one of a number of server devicesforming part of the messaging server system 108. In some examples, themachine 1000 may also comprise both client and server systems, withcertain operations of a particular method or algorithm being performedon the server-side and with certain operations of the particular methodor algorithm being performed on the client-side.

The machine 1000 may include processors 1002, memory 1004, andinput/output (I/O) components 1038, which may be configured tocommunicate with each other via a bus 1040. In an example, theprocessors 1002 (e.g., a Central Processing Unit (CPU), a ReducedInstruction Set Computing (RISC) Processor, a Complex Instruction SetComputing (CISC) Processor, a Graphics Processing Unit (GPU), a DigitalSignal Processor (DSP), an Application Specific Integrated Circuit(ASIC), a Radio-Frequency Integrated Circuit (RFIC), another processor,or any suitable combination thereof) may include, for example, aprocessor 1006 and a processor 1010 that execute the instructions 1008.The term “processor” is intended to include multi-core processors thatmay comprise two or more independent processors (sometimes referred toas “cores”) that may execute instructions contemporaneously. AlthoughFIG. 10 shows multiple processors 1002, the machine 1000 may include asingle processor with a single-core, a single processor with multiplecores (e.g., a multi-core processor), multiple processors with a singlecore, multiple processors with multiples cores, or any combinationthereof.

The memory 1004 includes a main memory 1012, a static memory 1014, and astorage unit 1016, all accessible to the processors 1002 via the bus1040. The main memory 1004, the static memory 1014, and the storage unit1016 store the instructions 1008 embodying any one or more of themethodologies or functions described herein. The instructions 1008 mayalso reside, completely or partially, within the main memory 1012,within the static memory 1014, within machine-readable medium within thestorage unit 1016, within at least one of the processors 1002 (e.g.,within the processor's cache memory), or any suitable combinationthereof, during execution thereof by the machine 1000.

The I/O components 1038 may include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 1038 that are included in a particular machine will depend onthe type of machine. For example, portable machines such as mobilephones may include a touch input device or other such input mechanisms,while a headless server machine will likely not include such a touchinput device. It will be appreciated that the I/O components 1038 mayinclude many other components that are not shown in FIG. 10 . In variousexamples, the I/O components 1038 may include user output components1024 and user input components 1026. The user output components 1024 mayinclude visual components (e.g., a display such as a plasma displaypanel (PDP), a light-emitting diode (LED) display, a liquid crystaldisplay (LCD), a projector, or a cathode ray tube (CRT)), acousticcomponents (e.g., speakers), haptic components (e.g., a vibratory motor,resistance mechanisms), other signal generators, and so forth. The userinput components 1026 may include alphanumeric input components (e.g., akeyboard, a touch screen configured to receive alphanumeric input, aphoto-optical keyboard, or other alphanumeric input components),point-based input components (e.g., a mouse, a touchpad, a trackball, ajoystick, a motion sensor, or another pointing instrument), tactileinput components (e.g., a physical button, a touch screen that provideslocation and force of touches or touch gestures, or other tactile inputcomponents), audio input components (e.g., a microphone), and the like.

In further examples, the I/O components 1038 may include biometriccomponents 1028, motion components 1030, environmental components 1032,or position components 1034, among a wide array of other components. Forexample, the biometric components 1028 include components to detectexpressions (e.g., hand expressions, facial expressions, vocalexpressions, body gestures, or eye-tracking), measure biosignals (e.g.,blood pressure, heart rate, body temperature, perspiration, or brainwaves), identify a person (e.g., voice identification, retinalidentification, facial identification, fingerprint identification, orelectroencephalogram-based identification), and the like. The motioncomponents 1030 include acceleration sensor components (e.g.,accelerometer), gravitation sensor components, rotation sensorcomponents (e.g., gyroscope).

The environmental components 1032 include, for example, one or morecameras (with still image/photograph and video capabilities),illumination sensor components (e.g., photometer), temperature sensorcomponents (e.g., one or more thermometers that detect ambienttemperature), humidity sensor components, pressure sensor components(e.g., barometer), acoustic sensor components (e.g., one or moremicrophones that detect background noise), proximity sensor components(e.g., infrared sensors that detect nearby objects), gas sensors (e.g.,gas detection sensors to detection concentrations of hazardous gases forsafety or to measure pollutants in the atmosphere), or other componentsthat may provide indications, measurements, or signals corresponding toa surrounding physical environment.

With respect to cameras, the client device 102 may have a camera systemcomprising, for example, front cameras on a front surface of the clientdevice 102 and rear cameras on a rear surface of the client device 102.The front cameras may, for example, be used to capture still images andvideo of a user of the client device 102 (e.g., “selfies”), which maythen be augmented with augmentation data (e.g., filters) describedabove. The rear cameras may, for example, be used to capture stillimages and videos in a more traditional camera mode, with these imagessimilarly being augmented with augmentation data. In addition to frontand rear cameras, the client device 102 may also include a 360° camerafor capturing 360° photographs and videos.

Further, the camera system of a client device 102 may include dual rearcameras (e.g., a primary camera as well as a depth-sensing camera), oreven triple, quad, or penta rear camera configurations on the front andrear sides of the client device 102. These multiple cameras systems mayinclude a wide camera, an ultra-wide camera, a telephoto camera, a macrocamera, and a depth sensor, for example.

The position components 1034 include location sensor components (e.g., aGPS receiver component), altitude sensor components (e.g., altimeters orbarometers that detect air pressure from which altitude may be derived),orientation sensor components (e.g., magnetometers), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 1038 further include communication components 1036operable to couple the machine 1000 to a network 1020 or devices 1022via respective coupling or connections. For example, the communicationcomponents 1036 may include a network interface component or anothersuitable device to interface with the network 1020. In further examples,the communication components 1036 may include wired communicationcomponents, wireless communication components, cellular communicationcomponents, Near Field Communication (NFC) components, Bluetooth®components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and othercommunication components to provide communication via other modalities.The devices 1022 may be another machine or any of a wide variety ofperipheral devices (e.g., a peripheral device coupled via a USB).

Moreover, the communication components 1036 may detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 1036 may include Radio Frequency Identification(RFID) tag reader components, NFC smart tag detection components,optical reader components (e.g., an optical sensor to detectone-dimensional bar codes such as Universal Product Code (UPC) bar code,multi-dimensional bar codes such as Quick Response (QR) code, Azteccode, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2Dbar code, and other optical codes), or acoustic detection components(e.g., microphones to identify tagged audio signals). In addition, avariety of information may be derived via the communication components1036, such as location via Internet Protocol (IP) geolocation, locationvia Wi-Fi® signal triangulation, location via detecting an NFC beaconsignal that may indicate a particular location, and so forth.

The various memories (e.g., main memory 1012, static memory 1014, andmemory of the processors 1002) and storage unit 1016 may store one ormore sets of instructions and data structures (e.g., software) embodyingor used by any one or more of the methodologies or functions describedherein. These instructions (e.g., the instructions 1008), when executedby processors 1002, cause various operations to implement the disclosedexamples.

The instructions 1008 may be transmitted or received over the network1020, using a transmission medium, via a network interface device (e.g.,a network interface component included in the communication components1036) and using any one of several well-known transfer protocols (e.g.,HTTP). Similarly, the instructions 1008 may be transmitted or receivedusing a transmission medium via a coupling (e.g., a peer-to-peercoupling) to the devices 1022.Software Architecture

FIG. 11 is a block diagram 1100 illustrating a software architecture1104, which can be installed on any one or more of the devices describedherein. The software architecture 1104 is supported by hardware such asa machine 1102 that includes processors 1120, memory 1126, and I/Ocomponents 1138. In this example, the software architecture 1104 can beconceptualized as a stack of layers, where each layer provides aparticular functionality. The software architecture 1104 includes layerssuch as an operating system 1112, libraries 1110, frameworks 1108, andapplications. Operationally, the applications 1106 invoke API calls 1150through the software stack and receive messages 1152 in response to theAPI calls 1150.

The operating system 1112 manages hardware resources and provides commonservices. The operating system 1112 includes, for example, a kernel1114, services 1116, and drivers 1122. The kernel 1114 acts as anabstraction layer between the hardware and the other software layers.For example, the kernel 1114 provides memory management, processormanagement (e.g., scheduling), component management, networking, andsecurity settings, among other functionality. The services 1116 canprovide other common services for the other software layers. The drivers1122 are responsible for controlling or interfacing with the underlyinghardware. For instance, the drivers 1122 can include display drivers,camera drivers, BLUETOOTH® or BLUETOOTH® Low Energy drivers, flashmemory drivers, serial communication drivers (e.g., USB drivers), WI-FI®drivers, audio drivers, power management drivers, and so forth.

The libraries 1110 provide a common low-level infrastructure used byapplications 1106. The libraries 1110 can include system libraries 1118(e.g., C standard library) that provide functions such as memoryallocation functions, string manipulation functions, mathematicfunctions, and the like. In addition, the libraries 1110 can include APIlibraries 1124 such as media libraries (e.g., libraries to supportpresentation and manipulation of various media formats such as MovingPicture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC),Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC),Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group(JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries(e.g., an OpenGL framework used to render in 2D and 3) in a graphiccontent on a display), database libraries (e.g., SQLite to providevarious relational database functions), web libraries (e.g., WebKit toprovide web browsing functionality), and the like. The libraries 1110can also include a wide variety of other libraries 1128 to provide manyother APIs to the applications 1106.

The frameworks 1108 provide a common high-level infrastructure that isused by the applications 1106. For example, the frameworks 1108 providevarious graphical user interface functions, high-level resourcemanagement, and high-level location services. The frameworks 1108 canprovide a broad spectrum of other APIs that can be used by theapplications 1106, some of which may be specific to a particularoperating system or platform.

In an example, the applications 1106 may include a home application1136, a contacts application 1130, a browser application 1132, a bookreader application 1134, a location application 1142, a mediaapplication 1144, a messaging application 1146, a game application 1148,and a broad assortment of other applications such as an externalapplication 1140. The applications 1106 are programs that executefunctions defined in the programs. Various programming languages can beemployed to create one or more of the applications 1106, structured in avariety of manners, such as object-oriented programming languages (e.g.,Objective-C, Java, or C++) or procedural programming languages (e.g., Cor assembly language). In a specific example, the external application1140 (e.g., an application developed using the ANDROID™ or IOS™ SDK byan entity other than the vendor of the particular platform) may bemobile software running on a mobile operating system such as IOS™,ANDROID™, WINDOWS® Phone, or another mobile operating system. In thisexample, the external application 1140 can invoke the API calls 1150provided by the operating system 1112 to facilitate functionalitydescribed herein.

Glossary

“Carrier signal” refers to any intangible medium that is capable ofstoring, encoding, or carrying instructions for execution by themachine, and includes digital or analog communications signals or otherintangible media to facilitate communication of such instructions.Instructions may be transmitted or received over a network using atransmission medium via a network interface device.

“Client device” refers to any machine that interfaces to acommunications network to obtain resources from one or more serversystems or other client devices. A client device may be, but is notlimited to, a mobile phone, desktop computer, laptop, PDAs, smartphones,tablets, ultrabooks, netbooks, laptops, multi-processor systems,microprocessor-based or programmable consumer electronics, gameconsoles, set-top boxes, or any other communication device that a usermay use to access a network.

“Communication network” refers to one or more portions of a network thatmay be an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local area network (LAN), a wireless LAN (WLAN), a widearea network (WAN), a wireless WAN (WWAN), a metropolitan area network(MAN), the Internet, a portion of the Internet, a portion of the PublicSwitched Telephone Network (PSTN), a plain old telephone service (POTS)network, a cellular telephone network, a wireless network, a Wi-Fi®network, another type of network, or a combination of two or more suchnetworks. For example, a network or a portion of a network may include awireless or cellular network and the coupling may be a Code DivisionMultiple Access (CDMA) connection, a Global System for Mobilecommunications (GSM) connection, or other types of cellular or wirelesscoupling. In this example, the coupling may implement any of a varietyof types of data transfer technology, such as Single Carrier RadioTransmission Technology (1×RTT), Evolution-Data Optimized (EVDO)technology, General Packet Radio Service (GPRS) technology, EnhancedData rates for GSM Evolution (EDGE) technology, third GenerationPartnership Project (3GPP) including 3G, fourth generation wireless (4G)networks, Universal Mobile Telecommunications System (UMTS), High SpeedPacket Access (HSPA), Worldwide Interoperability for Microwave Access(WiMAX), Long Term Evolution (LTE) standard, others defined by variousstandard-setting organizations, other long-range protocols, or otherdata transfer technology.

“Component” refers to a device, physical entity, or logic havingboundaries defined by function or subroutine calls, branch points, APIs,or other technologies that provide for the partitioning ormodularization of particular processing or control functions. Componentsmay be combined via their interfaces with other components to carry outa machine process. A component may be a packaged functional hardwareunit designed for use with other components and a part of a program thatusually performs a particular function of related functions.

Components may constitute either software components (e.g., codeembodied on a machine-readable medium) or hardware components. A“hardware component” is a tangible unit capable of performing certainoperations and may be configured or arranged in a certain physicalmanner. In various examples, one or more computer systems (e.g., astandalone computer system, a client computer system, or a servercomputer system) or one or more hardware components of a computer system(e.g., a processor or a group of processors) may be configured bysoftware (e.g., an application or application portion) as a hardwarecomponent that operates to perform certain operations as describedherein.

A hardware component may also be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware component may include dedicated circuitry or logic that ispermanently configured to perform certain operations. A hardwarecomponent may be a special-purpose processor, such as afield-programmable gate array (FPGA) or an ASIC. A hardware componentmay also include programmable logic or circuitry that is temporarilyconfigured by software to perform certain operations. For example, ahardware component may include software executed by a general-purposeprocessor or other programmable processor. Once configured by suchsoftware, hardware components become specific machines (or specificcomponents of a machine) uniquely tailored to perform the configuredfunctions and are no longer general-purpose processors. It will beappreciated that the decision to implement a hardware componentmechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software), may bedriven by cost and time considerations. Accordingly, the phrase“hardware component” (or “hardware-implemented component”) should beunderstood to encompass a tangible entity, be that an entity that isphysically constructed, permanently configured (e.g., hardwired), ortemporarily configured (e.g., programmed) to operate in a certain manneror to perform certain operations described herein.

Considering examples in which hardware components are temporarilyconfigured (e.g., programmed), each of the hardware components need notbe configured or instantiated at any one instance in time. For example,where a hardware component comprises a general-purpose processorconfigured by software to become a special-purpose processor, thegeneral-purpose processor may be configured as respectively differentspecial-purpose processors (e.g., comprising different hardwarecomponents) at different times. Software accordingly configures aparticular processor or processors, for example, to constitute aparticular hardware component at one instance of time and to constitutea different hardware component at a different instance of time.

Hardware components can provide information to, and receive informationfrom, other hardware components. Accordingly, the described hardwarecomponents may be regarded as being communicatively coupled. Wheremultiple hardware components exist contemporaneously, communications maybe achieved through signal transmission (e.g., over appropriate circuitsand buses) between or among two or more of the hardware components. Inexamples in which multiple hardware components are configured orinstantiated at different times, communications between such hardwarecomponents may be achieved, for example, through the storage andretrieval of information in memory structures to which the multiplehardware components have access. For example, one hardware component mayperform an operation and store the output of that operation in a memorydevice to which it is communicatively coupled. A further hardwarecomponent may then, at a later time, access the memory device toretrieve and process the stored output. Hardware components may alsoinitiate communications with input or output devices, and can operate ona resource (e.g., a collection of information).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implementedcomponents that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented component”refers to a hardware component implemented using one or more processors.Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method may be performed by one or more processors 1002 orprocessor-implemented components. Moreover, the one or more processorsmay also operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations may be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an API). The performance ofcertain of the operations may be distributed among the processors, notonly residing within a single machine, but deployed across a number ofmachines. In some examples, the processors or processor-implementedcomponents may be located in a single geographic location (e.g., withina home environment, an office environment, or a server farm). In otherexamples, the processors or processor-implemented components may bedistributed across a number of geographic locations.

“Computer-readable storage medium” refers to both machine-storage mediaand transmission media. Thus, the terms include both storagedevices/media and carrier waves/modulated data signals. The terms“machine-readable medium,” “computer-readable medium,” and“device-readable medium” mean the same thing and may be usedinterchangeably in this disclosure.

“Ephemeral message” refers to a message that is accessible for atime-limited duration. An ephemeral message may be a text, an image, avideo, and the like. The access time for the ephemeral message may beset by the message sender. Alternatively, the access time may be adefault setting or a setting specified by the recipient. Regardless ofthe setting technique, the message is transitory.

“Machine storage medium” refers to a single or multiple storage devicesand media (e.g., a centralized or distributed database, and associatedcaches and servers) that store executable instructions, routines anddata. The term shall accordingly be taken to include, but not be limitedto, solid-state memories, and optical and magnetic media, includingmemory internal or external to processors. Specific examples ofmachine-storage media, computer-storage media and device-storage mediainclude non-volatile memory, including by way of example semiconductormemory devices, e.g., erasable programmable read-only memory (EPROM),electrically erasable programmable read-only memory (EEPROM), FPGA, andflash memory devices; magnetic disks such as internal hard disks andremovable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks Theterms “machine-storage medium,” “device-storage medium,”“computer-storage medium” mean the same thing and may be usedinterchangeably in this disclosure. The terms “machine-storage media,”“computer-storage media,” and “device-storage media” specificallyexclude carrier waves, modulated data signals, and other such media, atleast some of which are covered under the term “signal medium.”

“Non-transitory computer-readable storage medium” refers to a tangiblemedium that is capable of storing, encoding, or carrying theinstructions for execution by a machine.

“Signal medium” refers to any intangible medium that is capable ofstoring, encoding, or carrying the instructions for execution by amachine and includes digital or analog communications signals or otherintangible media to facilitate communication of software or data. Theterm “signal medium” shall be taken to include any form of a modulateddata signal, carrier wave, and so forth. The term “modulated datasignal” means a signal that has one or more of its characteristics setor changed in such a matter as to encode information in the signal. Theterms “transmission medium” and “signal medium” mean the same thing andmay be used interchangeably in this disclosure.

Changes and modifications may be made to the disclosed examples withoutdeparting from the scope of the present disclosure. These and otherchanges or modifications are intended to be included within the scope ofthe present disclosure, as expressed in the following claims.

What is claimed is:
 1. A method comprising: generating, by one or moreprocessors, a three-dimensional (3D) mesh associated with a real-worldobject that tracks movement of the real-world object; obtaining anexternal mesh associated with an augmented reality (AR) element;accessing a plurality of deformation attributes associated with theexternal mesh, each of the plurality of deformation attributescorresponding to a different deformation model; separately deforming,based on respective deformation models, a first portion of the externalmesh associated with a first of the plurality of deformation attributesand a second portion of the external mesh associated with a second ofthe plurality of deformation attributes; and modifying a video thatincludes a depiction of the real-world object to include a display ofthe AR element based on the first and second portions of the externalmesh that have been separately deformed.
 2. The method of claim 1,further comprising: determining that the first portion of the externalmesh is associated with the first of the plurality of deformationattributes; and determining that the second portion of the external meshis associated with the second of the plurality of deformationattributes.
 3. The method of claim 1, the 3D mesh comprising a 3D bodymesh, further comprising: automatically establishing a correspondencebetween the 3D body mesh associated with the real-world object and theexternal mesh, wherein the real-world object comprises a person; andwherein the 3D body mesh represents a whole body of the person depictedin the video.
 4. The method of claim 3, wherein the first of theplurality of deformation attributes comprises a distance threshold,further comprising: computing a distance between a vertex in the firstportion of the external mesh and a first edge of the 3D body meshcorresponding to the first portion of the external mesh; determiningthat the distance between the vertex in the first portion of theexternal mesh and the first edge of the 3D body mesh exceeds thedistance threshold; and in response to determining that the distancebetween the vertex in the first portion of the external mesh and thefirst edge of the 3D body mesh exceeds the distance threshold, deformingthe first portion of the external mesh based on a first of therespective deformation models.
 5. The method of claim 4, furthercomprising: computing a distance between a vertex in the second portionof the external mesh and a second edge of the 3D body mesh correspondingto the second portion of the external mesh; determining that thedistance between the vertex in the second portion of the external meshand the second edge of the 3D body mesh is less than the distancethreshold; and in response to determining that the distance between thevertex in the second portion of the external mesh and the second edge ofthe 3D body mesh is less than the distance threshold, deforming thesecond portion of the external mesh based on a second of the respectivedeformation models.
 6. The method of claim 5, wherein the first of therespective deformation models comprises an external force model, andwherein the second of the respective deformation models comprises amovement model representing movement of the 3D body mesh.
 7. The methodof claim 6, wherein the external force model is defined by at least oneof a physics simulation, a collision simulation, chain physics, or acloth simulation.
 8. The method of claim 3, wherein the first of theplurality of deformation attributes comprises a body mesh densitythreshold, further comprising: computing a density of pixels within afirst portion of the 3D body mesh corresponding to the first portion ofthe external mesh; determining that the density of the pixels within thefirst portion of the 3D body mesh exceeds the body mesh densitythreshold; and in response to determining that the density of the pixelswithin the first portion of the 3D body mesh exceeds the body meshdensity threshold, deforming the first portion of the external meshbased on a first of the respective deformation models.
 9. The method ofclaim 8, further comprising: computing a density of pixels within asecond portion of the 3D body mesh corresponding to the second portionof the external mesh; determining that the density of the pixels withinthe second portion of the 3D body mesh is less than the body meshdensity threshold; and in response to determining that the density ofthe pixels within the second portion of the 3D body mesh is less thanthe body mesh density threshold, deforming the second portion of theexternal mesh based on a second of the respective deformation models.10. The method of claim 9, wherein the first of the respectivedeformation models comprises a movement model representing movement ofthe 3D body mesh, and wherein the second of the respective deformationmodels comprises an external force model.
 11. The method of claim 1,wherein the first of the plurality of deformation attributes correspondsto a garment looseness metric, wherein the first portion of the externalmesh is deformed based on an external force model in response todetermining that the first portion of the external mesh satisfies thegarment looseness metric.
 12. The method of claim 1, wherein the firstof the plurality of deformation attributes corresponds to a garmentlocation metric, wherein the first portion of the external mesh isdeformed based on an external force model in response to determiningthat the first portion of the external mesh satisfies the garmentlocation metric, wherein the second portion of the external mesh isdeformed based on a body movement model in response to determining thatthe second portion of the external mesh fails to satisfy the garmentlocation metric.
 13. The method of claim 12, wherein the garmentlocation metric is satisfied in response to determining that the firstportion of the external mesh corresponds to a first portion of the 3Dmesh, and wherein the second portion of the external mesh fails tosatisfy the garment location metric in response to determining that thefirst portion of the external mesh corresponds to a second portion ofthe 3D mesh.
 14. The method of claim 13, wherein the first portion ofthe 3D mesh comprises legs and wherein the second portion of the 3D meshcomprises a torso.
 15. The method of claim 12, wherein the garmentlocation metric represents a distance between a given portion of theexternal mesh relative to a torso portion of the 3D mesh.
 16. The methodof claim 1, wherein: the first of the plurality of deformationattributes corresponds to at least one of a garment location metric, agarment looseness metric, a body mesh density threshold, or a distancethreshold; and the second of the plurality of deformation attributescorresponds to at least a different one of the garment location metric,the garment looseness metric, the body mesh density threshold, or thedistance threshold.
 17. The method of claim 1, further comprisingobtaining placement information for the external mesh that describes theplurality of deformation attributes indicating which portions of theexternal mesh are deformed based on movement of the real-world objectand which portions of the external mesh are deformed or controlled basedon an external force model.
 18. The method of claim 1, furthercomprising: determining a first set of coordinates of the 3D mesh in anormal-tangent space for a first frame of the frames of the video;determining a second set of coordinates of the 3D mesh in thenormal-tangent space for a second frame of the frames of the video;computing, in real time, a change between the first and second sets ofcoordinates in the normal-tangent space; and transferring the changebetween the first and second sets of coordinates in the normal-tangentspace to the first portion or the second portion of the external mesh.19. A system comprising: a processor of a client device; and a memorycomponent having instructions stored thereon that, when executed by theprocessor, cause the processor to perform operations comprising:obtaining an external mesh associated with an augmented reality (AR)element; accessing a plurality of deformation attributes associated withthe external mesh, each of the plurality of deformation attributescorresponding to a different deformation model; separately deforming,based on respective deformation models, a first portion of the externalmesh associated with a first of the plurality of deformation attributesand a second portion of the external mesh associated with a second ofthe plurality of deformation attributes; and modifying a video thatincludes a depiction of a real-world object to include a display of theAR element based on the first and second portions of the external meshthat have been separately deformed.
 20. A non-transitorycomputer-readable storage medium having stored thereon instructionsthat, when executed by a processor of a client device, cause theprocessor to perform operations comprising: obtaining an external meshassociated with an augmented reality (AR) element; accessing a pluralityof deformation attributes associated with the external mesh, each of theplurality of deformation attributes corresponding to a differentdeformation model; separately deforming, based on respective deformationmodels, a first portion of the external mesh associated with a first ofthe plurality of deformation attributes and a second portion of theexternal mesh associated with a second of the plurality of deformationattributes; and modifying a video that includes a depiction of areal-world object to include a display of the AR element based on thefirst and second portions of the external mesh that have been separatelydeformed.